Prof. PhD DSc Eng
Leszek Rutkowski
Papers (200)
2026 (29)
Tang T., Cheng J., Shi M., Zhang D., Basin M.V., Rutkowski L., Switching Rule Design for Dual-Channel Data Transmission in Discrete-Time Fuzzy Systems. (0)
Switching Rule Design for Dual-Channel Data Transmission in Discrete-Time Fuzzy Systems
, Switching Rule Design for Dual-Channel Data Transmission in Discrete-Time Fuzzy Systems, IEEE Transactions on Systems Man and Cybernetics Systems, 56, 56, 999-1008, 2026, Cites: 0
Zhang G., Shen H., Wang J., Cao J., Rutkowski L., Resilient H∞ Output Feedback Control for Hidden Semi-Markov Jump Systems Subject to Hybrid Cyber Attacks. (1)
Resilient H∞ Output Feedback Control for Hidden Semi-Markov Jump Systems Subject to Hybrid Cyber Attacks
, Resilient H∞ Output Feedback Control for Hidden Semi-Markov Jump Systems Subject to Hybrid Cyber Attacks, IEEE Internet of Things Journal, 13, 13, 13072-13081, 2026, Cites: 1
Zhang J., Cao J., Rutkowski L., Shi X., Accelerated Transfer-Entropy-Weighted ADMM for Learning Causal Directed Acyclic Graphs. (0)
Accelerated Transfer-Entropy-Weighted ADMM for Learning Causal Directed Acyclic Graphs
, Accelerated Transfer-Entropy-Weighted ADMM for Learning Causal Directed Acyclic Graphs, IEEE Transactions on Network Science and Engineering, 2026, Cites: 0
Zhang B., Bao W., Cheng J., Rutkowski L., Zhang D., Yan H., Shen Y., Observer-Based Adaptive Neural Sliding Mode Control of Fuzzy Systems with Sojourn-Probability-Based Multimode Attacks. (0)
Observer-Based Adaptive Neural Sliding Mode Control of Fuzzy Systems with Sojourn-Probability-Based Multimode Attacks
, Observer-Based Adaptive Neural Sliding Mode Control of Fuzzy Systems with Sojourn-Probability-Based Multimode Attacks, IEEE Transactions on Cybernetics, 56, 56, 2364-2373, 2026, Cites: 0
Chen S., Wan Y., Rutkowski L., Hua L., Cao J., Nash Equilibrium Seeking for Hybrid Heterogeneous Euler–Lagrange Systems in Multicluster Games Under DoS Attacks: A Predefined-Time Approach. (0)
Nash Equilibrium Seeking for Hybrid Heterogeneous Euler–Lagrange Systems in Multicluster Games Under DoS Attacks: A Predefined-Time Approach
, Nash Equilibrium Seeking for Hybrid Heterogeneous Euler–Lagrange Systems in Multicluster Games Under DoS Attacks: A Predefined-Time Approach, IEEE Transactions on Computational Social Systems, 2026, Cites: 0
Wang H., Jing Y., Sun H., Wang J., Liao J., Rutkowski L., Tao D., Bridging the Tokenizer Gap: Semantics and Distribution-aware Knowledge Transfer for Unbiased Cross-Tokenizer Distillation. (0)
Bridging the Tokenizer Gap: Semantics and Distribution-aware Knowledge Transfer for Unbiased Cross-Tokenizer Distillation
, Bridging the Tokenizer Gap: Semantics and Distribution-aware Knowledge Transfer for Unbiased Cross-Tokenizer Distillation, Proceedings of the Aaai Conference on Artificial Intelligence, 40, 40, 33494-33502, 2026, Cites: 0
Li Z., Zhu X., Cao J., Shi X., Yu X., Rutkowski L., Huang W., Multi-evolutionary stage modeling of rutting depth based on meta-inspiration algorithm and random enhancement XGBoost. (0)
Multi-evolutionary stage modeling of rutting depth based on meta-inspiration algorithm and random enhancement XGBoost
, Multi-evolutionary stage modeling of rutting depth based on meta-inspiration algorithm and random enhancement XGBoost, Construction and Building Materials, 514, 514, 2026, Cites: 0
Rao H., Li Z., Yang L., Xu Y., Huang T., Rutkowski L., Optimal Hybrid Transmission Strategy for Remote State Estimation With Deep Reinforcement Learning. (0)
Optimal Hybrid Transmission Strategy for Remote State Estimation With Deep Reinforcement Learning
, Optimal Hybrid Transmission Strategy for Remote State Estimation With Deep Reinforcement Learning, IEEE Transactions on Systems Man and Cybernetics Systems, 56, 56, 849-860, 2026, Cites: 0
Sevastjanov P., Kaczmarek K., Dymova L., Rutkowski L., An approach to the dynamic fuzzy multi-criteria multi-currency money management on the currency exchange market. (0)
An approach to the dynamic fuzzy multi-criteria multi-currency money management on the currency exchange market
, An approach to the dynamic fuzzy multi-criteria multi-currency money management on the currency exchange market, Expert Systems with Applications, 308, 308, 2026, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15950 LNCS, 15950 LNCS, v, 2026, Cites: 0
Tian Y., Xue P., Ding W., Hassaballah M., Egiazarian K., Conci A., Sengur A., Rutkowski L., DM-CFO: A Diffusion Model for Compositional 3D Tooth Generation with Collision-Free Optimization. (0)
DM-CFO: A Diffusion Model for Compositional 3D Tooth Generation with Collision-Free Optimization
, DM-CFO: A Diffusion Model for Compositional 3D Tooth Generation with Collision-Free Optimization, IEEE Transactions on Visualization and Computer Graphics, 2026, Cites: 0
Yang Q., Zhong Y., Liu C., Xu Y., Huang T., Rutkowski L., Partial-Nodes-Based Estimation for Complex Networks With Random Inner Coupling. (0)
Partial-Nodes-Based Estimation for Complex Networks With Random Inner Coupling
, Partial-Nodes-Based Estimation for Complex Networks With Random Inner Coupling, IEEE Transactions on Systems Man and Cybernetics Systems, 56, 56, 481-491, 2026, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15949 LNCS, 15949 LNCS, v, 2026, Cites: 0
Bao R., Wang B., Wang X., Li H., Zheng R., Rutkowski L., Zhang Q., Ding L., Tao D., Time-Frequency Token Advantage Clipping for Training Efficient Large Reasoning Model. (0)
Time-Frequency Token Advantage Clipping for Training Efficient Large Reasoning Model
, Time-Frequency Token Advantage Clipping for Training Efficient Large Reasoning Model, Proceedings of the Aaai Conference on Artificial Intelligence, 40, 40, 30049-30057, 2026, Cites: 0
Zhang B., Tang X., Cheng J., Luo M., Zhang D., Rutkowski L., Yan M., Secure Dynamic Output Feedback Control of Fuzzy Multi-Rate Systems Under Important Data-Based Attacks. (0)
Secure Dynamic Output Feedback Control of Fuzzy Multi-Rate Systems Under Important Data-Based Attacks
, Secure Dynamic Output Feedback Control of Fuzzy Multi-Rate Systems Under Important Data-Based Attacks, IEEE Transactions on Automation Science and Engineering, 23, 23, 6042-6051, 2026, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15948 LNCS, 15948 LNCS, v, 2026, Cites: 0
Xu S., Liang S., Zheng H., Liu A., Wang X., Luo Y., Lin F., Rutkowski L., Tao D., SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs. (0)
SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs
, SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs, Proceedings of the Aaai Conference on Artificial Intelligence, 40, 40, 11397-11405, 2026, Cites: 0
Dong S., Xiao M., Wang Z., Yu W., Zheng W., Rutkowski L., Pattern Optimization of Fractional Diffusive Schnakenberg System by PD Control Strategy. (0)
Pattern Optimization of Fractional Diffusive Schnakenberg System by PD Control Strategy
, Pattern Optimization of Fractional Diffusive Schnakenberg System by PD Control Strategy, IEEE Caa Journal of Automatica Sinica, 13, 13, 451-462, 2026, Cites: 0
Li H., Xiao M., Huang C., Fang Q., Huang X., Yu W., Yao Y., Huang T., Rutkowski L., Dynamic Reinforcement Learning Control for Fractional-Order Neural Networks with Higher-Order Interactions and Multiple Time Delays. (0)
Dynamic Reinforcement Learning Control for Fractional-Order Neural Networks with Higher-Order Interactions and Multiple Time Delays
, Dynamic Reinforcement Learning Control for Fractional-Order Neural Networks with Higher-Order Interactions and Multiple Time Delays, IEEE Transactions on Artificial Intelligence, 2026, Cites: 0
Xu Y., Cheng J., Wang Y., He S., Rutkowski L., Second-Order Sliding Mode Optimal Control for Two-Dimensional Systems Under Dynamic Binary Encoding. (0)
Second-Order Sliding Mode Optimal Control for Two-Dimensional Systems Under Dynamic Binary Encoding
, Second-Order Sliding Mode Optimal Control for Two-Dimensional Systems Under Dynamic Binary Encoding, IEEE Transactions on Fuzzy Systems, 34, 34, 273-285, 2026, Cites: 0
Sakthivel R., Kaviarasan B., Rutkowski L., Huynh V.T., Resilient filtering of fuzzy multi-weighted complex dynamical networks against cyber attacks and missing measurements. (0)
Resilient filtering of fuzzy multi-weighted complex dynamical networks against cyber attacks and missing measurements
, Resilient filtering of fuzzy multi-weighted complex dynamical networks against cyber attacks and missing measurements, Communications in Nonlinear Science and Numerical Simulation, 157, 157, 2026, Cites: 0
Smendowski M., Wojtulewicz M., Nawrocki P., Rutkowski L., A Novel Balanced Binary Whale Optimization Algorithm for Dynamic Feature Selection in Green Cloud Computing. (0)
A Novel Balanced Binary Whale Optimization Algorithm for Dynamic Feature Selection in Green Cloud Computing
, A Novel Balanced Binary Whale Optimization Algorithm for Dynamic Feature Selection in Green Cloud Computing, IEEE Transactions on Cloud Computing, 2026, Cites: 0
He H., Xiao M., Cao J., Zhou Y., Park J.H., Rutkowski L., Fractional Gierer-Meinhardt system with cross-diffusion: Pattern analysis in three-dimensional space. (0)
Fractional Gierer-Meinhardt system with cross-diffusion: Pattern analysis in three-dimensional space
, Fractional Gierer-Meinhardt system with cross-diffusion: Pattern analysis in three-dimensional space, Applied Mathematics and Computation, 513, 513, 2026, Cites: 0
Li H., Xiao M., Rutkowski L., Wan Y.-H., Cross-diffusion research of a class of Gierer-Meinhardt models with saturation terms. (0)
Cross-diffusion research of a class of Gierer-Meinhardt models with saturation terms
, Cross-diffusion research of a class of Gierer-Meinhardt models with saturation terms, Kongzhi Lilun Yu Yingyong Control Theory and Applications, 43, 43, 561-572, 2026, Cites: 0
Bao S., Li J., Liu C., Xu Y., Huang T., Rutkowski L., Distributed Set-Membership Estimation Over Delayed and Attacked Sensor Networks. (0)
Distributed Set-Membership Estimation Over Delayed and Attacked Sensor Networks
, Distributed Set-Membership Estimation Over Delayed and Attacked Sensor Networks, IEEE Transactions on Industrial Cyber Physical Systems, 4, 4, 25-33, 2026, Cites: 0
Gao C., Qi R., Xiao Y., Rutkowski L., Adaptive noise control for almost sure exponential stability of stochastic coupled jump diffusion systems. (0)
Adaptive noise control for almost sure exponential stability of stochastic coupled jump diffusion systems
, Adaptive noise control for almost sure exponential stability of stochastic coupled jump diffusion systems, Communications in Nonlinear Science and Numerical Simulation, 157, 157, 2026, Cites: 0
Huang Y., Shi M., Cheng J., Yan M., Rutkowski L., Iterative Learning Security Control under Bit-Rate Constraints and Attacks. (0)
Iterative Learning Security Control under Bit-Rate Constraints and Attacks
, Iterative Learning Security Control under Bit-Rate Constraints and Attacks, IEEE Internet of Things Journal, 2026, Cites: 0
Duda P., Wojtulewicz M., Rutkowski L., Approximate Importance-Based Sampling for Neural Network Training. (0)
Approximate Importance-Based Sampling for Neural Network Training
, Approximate Importance-Based Sampling for Neural Network Training, Lecture Notes in Computer Science, 15948 LNCS, 15948 LNCS, 72-81, 2026, Cites: 0
Mei X., Huang W., Yan M., Cheng J., Rutkowski L., Dynamic binary encoding of 2-D fuzzy systems under importance-aware DoS attacks. (0)
Dynamic binary encoding of 2-D fuzzy systems under importance-aware DoS attacks
, Dynamic binary encoding of 2-D fuzzy systems under importance-aware DoS attacks, Fuzzy Sets and Systems, 539, 539, 2026, Cites: 02025 (24)
Cheng J., Liu N., Rutkowski L., Cao J., Yan H., Hua L., Space-Time Sampled-Data Control for Memristor- Based Reaction-Diffusion Neural Networks With Nonhomogeneous Sojourn Probabilities. (19)
Space-Time Sampled-Data Control for Memristor- Based Reaction-Diffusion Neural Networks With Nonhomogeneous Sojourn Probabilities
, Space-Time Sampled-Data Control for Memristor- Based Reaction-Diffusion Neural Networks With Nonhomogeneous Sojourn Probabilities, IEEE Transactions on Circuits and Systems I Regular Papers, 72, 72, 1452-1461, 2025, Cites: 19
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15165 LNAI, 15165 LNAI, v-vi, 2025, Cites: 0
Lu Y., Xiao M., Rutkowski L., Wang Z., Wu X., Wang Z., Huang C., Cao J., Xing Zheng W., How to Predict Bifurcations Induced by Fractional Order in Delayed Large-Scale Neural Networks. (3)
How to Predict Bifurcations Induced by Fractional Order in Delayed Large-Scale Neural Networks
, How to Predict Bifurcations Induced by Fractional Order in Delayed Large-Scale Neural Networks, IEEE Transactions on Cybernetics, 55, 55, 4400-4413, 2025, Cites: 3
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15164 LNAI, 15164 LNAI, v-vi, 2025, Cites: 0
Xia Y., Xiao K., Cao J., Lam H.-K., Precup R.-E., Rutkowski L., Agarwal R.K., Customized Non-Monotonic Prescribed Performance Control for Stochastic MEMS Gyroscopes With Insufficient Input Capability. (8)
Customized Non-Monotonic Prescribed Performance Control for Stochastic MEMS Gyroscopes With Insufficient Input Capability
, Customized Non-Monotonic Prescribed Performance Control for Stochastic MEMS Gyroscopes With Insufficient Input Capability, IEEE Transactions on Circuits and Systems I Regular Papers, 72, 72, 8184-8196, 2025, Cites: 8
Sevastjanov P., Kaczmarek K., Dymova L., Rutkowski L., Interpretable Forex trading models based on new technical analysis indicators and fuzzy multi-criteria optimization. (2)
Interpretable Forex trading models based on new technical analysis indicators and fuzzy multi-criteria optimization
, Interpretable Forex trading models based on new technical analysis indicators and fuzzy multi-criteria optimization, Fuzzy Sets and Systems, 511, 511, 2025, Cites: 2
Urbanczyk P., Urbanczyk A., Krol M., Rutkowski L., Kisiel-Dorohinicki M., Sequential, Parallel and Consecutive Hybrid Evolutionary-Swarm Optimization Metaheuristics. (1)
Sequential, Parallel and Consecutive Hybrid Evolutionary-Swarm Optimization Metaheuristics
, Sequential, Parallel and Consecutive Hybrid Evolutionary-Swarm Optimization Metaheuristics, Lecture Notes in Computer Science, 15907 LNCS, 15907 LNCS, 203-218, 2025, Cites: 1
Cheng J., Liu N., Rutkowski L., Cao J., Yan H., Protocol-Based Sampled-Data Control for T-S Fuzzy Reaction–Diffusion Neural Networks. (5)
Protocol-Based Sampled-Data Control for T-S Fuzzy Reaction–Diffusion Neural Networks
, Protocol-Based Sampled-Data Control for T-S Fuzzy Reaction–Diffusion Neural Networks, IEEE Transactions on Fuzzy Systems, 33, 33, 1168-1177, 2025, Cites: 5
Zhu P., Xiao M., Huang T., He H., Rutkowski L., Zheng W.X., Hybrid control strategy for the Lévy superdiffusion Sel’kov-Schnakenberg model: Formation, conversion, and annihilation of Turing patterns. (0)
Hybrid control strategy for the Lévy superdiffusion Sel’kov-Schnakenberg model: Formation, conversion, and annihilation of Turing patterns
, Hybrid control strategy for the Lévy superdiffusion Sel’kov-Schnakenberg model: Formation, conversion, and annihilation of Turing patterns, Chaos, 35, 35, 2025, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science, 15166 LNAI, 15166 LNAI, v-vi, 2025, Cites: 0
Kaczmarek K., Sevastjanov P., Dymova L., Kulawik A., Rutkowski L., A system of trading in the foreign exchange market based on multi-criteria optimization under Belief-Plausibility uncertainty. (2)
A system of trading in the foreign exchange market based on multi-criteria optimization under Belief-Plausibility uncertainty
, A system of trading in the foreign exchange market based on multi-criteria optimization under Belief-Plausibility uncertainty, Applied Soft Computing, 169, 169, 2025, Cites: 2
Li H., Yao Y., Xiao M., Wang Z., Rutkowski L., Turing pattern dynamics in a fractional-diffusion oregonator model under PD control. (2)
Turing pattern dynamics in a fractional-diffusion oregonator model under PD control
, Turing pattern dynamics in a fractional-diffusion oregonator model under PD control, Nonlinear Analysis Modelling and Control, 30, 30, 291-311, 2025, Cites: 2
Cheng J., Xu Y., Rutkowski L., Yan H., Cao J., Zhang B., Qiu X., Observer-Based Security Control for 2-D Fuzzy Switched Systems With Nonhomogeneous Sojourn Probabilities. (13)
Observer-Based Security Control for 2-D Fuzzy Switched Systems With Nonhomogeneous Sojourn Probabilities
, Observer-Based Security Control for 2-D Fuzzy Switched Systems With Nonhomogeneous Sojourn Probabilities, IEEE Transactions on Cybernetics, 55, 55, 3332-3341, 2025, Cites: 13
Xia Y., Xiao K., Cao J., Precup R.-E., Arya Y., Lam H.-K., Rutkowski L., Stochastic Neural Network Control for Stochastic Nonlinear Systems With Quadratic Local Asymmetric Prescribed Performance. (34)
Stochastic Neural Network Control for Stochastic Nonlinear Systems With Quadratic Local Asymmetric Prescribed Performance
, Stochastic Neural Network Control for Stochastic Nonlinear Systems With Quadratic Local Asymmetric Prescribed Performance, IEEE Transactions on Cybernetics, 55, 55, 867-879, 2025, Cites: 34
Gao C., Huang Y., Xiao Y., Rutkowski L., Almost sure synchronization of T-S fuzzy semi-Markov asynchronous switched systems under deception attacks. (1)
Almost sure synchronization of T-S fuzzy semi-Markov asynchronous switched systems under deception attacks
, Almost sure synchronization of T-S fuzzy semi-Markov asynchronous switched systems under deception attacks, Journal of the Franklin Institute, 362, 362, 2025, Cites: 1
Tang X., Cheng J., Zhang B., Rutkowski L., Huang W., Security Control for Fuzzy Singularly Perturbation Systems under DoS Attacks. (2)
Security Control for Fuzzy Singularly Perturbation Systems under DoS Attacks
, Security Control for Fuzzy Singularly Perturbation Systems under DoS Attacks, IEEE Transactions on Automation Science and Engineering, 22, 22, 19685-19693, 2025, Cites: 2
Zhang Q., Xu Y., Cheng J., Rutkowski L., Chen Y., Protocol-Based Reliable Control for 2-D Fuzzy Systems Subject to Fading Networks. (0)
Protocol-Based Reliable Control for 2-D Fuzzy Systems Subject to Fading Networks
, Protocol-Based Reliable Control for 2-D Fuzzy Systems Subject to Fading Networks, IEEE Transactions on Automation Science and Engineering, 22, 22, 22230-22238, 2025, Cites: 0
Liu J., Shen H., Wang J., Cao J., Rutkowski L., H∞ Control for Interconnected Systems With Unknown System Dynamics: A Two-Stage Reinforcement Learning Method. (8)
H∞ Control for Interconnected Systems With Unknown System Dynamics: A Two-Stage Reinforcement Learning Method
, H∞ Control for Interconnected Systems With Unknown System Dynamics: A Two-Stage Reinforcement Learning Method, IEEE Transactions on Automation Science and Engineering, 22, 22, 6388-6397, 2025, Cites: 8
Duda P., Wojtulewicz M., Nowicki R., Rutkowski L., Speedup of Training Deep Neural Networks in the Streaming Approach Using Genetic Algorithms with an Application of Drift Detection. (0)
Speedup of Training Deep Neural Networks in the Streaming Approach Using Genetic Algorithms with an Application of Drift Detection
, Speedup of Training Deep Neural Networks in the Streaming Approach Using Genetic Algorithms with an Application of Drift Detection, Lecture Notes in Computer Science, 15164 LNAI, 15164 LNAI, 62-75, 2025, Cites: 0
Kaczmarek K., Sevastjanov P., Dymova L., Kulawik A., Rutkowski L., A fuzzy three-criteria optimization-based currency trading system with adaptive criteria shapes and money management. (1)
A fuzzy three-criteria optimization-based currency trading system with adaptive criteria shapes and money management
, A fuzzy three-criteria optimization-based currency trading system with adaptive criteria shapes and money management, Engineering Applications of Artificial Intelligence, 159, 159, 2025, Cites: 1
Min F., Xiao M., Cao J., Wang Z., Ding J., Rutkowski L., Spatiotemporal dynamics of a food chain model incorporating higher-order interactions and slow–fast effect. (2)
Spatiotemporal dynamics of a food chain model incorporating higher-order interactions and slow–fast effect
, Spatiotemporal dynamics of a food chain model incorporating higher-order interactions and slow–fast effect, Chaos Solitons and Fractals, 199, 199, 2025, Cites: 2
Kaczmarek K., Dymova L., Sevastjanov P., Rutkowski L., Can volatility-dependent irregular forms of fuzzy local criteria increase the effectiveness of Forex trading models. (1)
Can volatility-dependent irregular forms of fuzzy local criteria increase the effectiveness of Forex trading models
, Can volatility-dependent irregular forms of fuzzy local criteria increase the effectiveness of Forex trading models, Expert Systems with Applications, 294, 294, 2025, Cites: 1
Xia Y., He J., Lam H.-K., Rutkowski L., Precup R.-E., Non-fragile fuzzy control of input-saturated systems with global prescribed performance via an error-triggered mechanism. (7)
Non-fragile fuzzy control of input-saturated systems with global prescribed performance via an error-triggered mechanism
, Non-fragile fuzzy control of input-saturated systems with global prescribed performance via an error-triggered mechanism, Information Sciences, 711, 711, 2025, Cites: 7
Wang J., Yang Q., Cao J., Rutkowski L., Shen H., Reinforcement-Learning-Based Fuzzy Bipartite Consensus for Multiagent Systems: A Novel Scaling Off-Policy Learning Scheme. (7)
Reinforcement-Learning-Based Fuzzy Bipartite Consensus for Multiagent Systems: A Novel Scaling Off-Policy Learning Scheme
, Reinforcement-Learning-Based Fuzzy Bipartite Consensus for Multiagent Systems: A Novel Scaling Off-Policy Learning Scheme, IEEE Transactions on Cybernetics, 55, 55, 4491-4501, 2025, Cites: 72024 (30)
Tao M., Guo L., Cao J., Rutkowski L., A Second-Order Primal-Dual Dynamics for Set Constrained Distributed Optimization Problems. (10)
A Second-Order Primal-Dual Dynamics for Set Constrained Distributed Optimization Problems
, A Second-Order Primal-Dual Dynamics for Set Constrained Distributed Optimization Problems, IEEE Transactions on Circuits and Systems II Express Briefs, 71, 71, 1316-1320, 2024, Cites: 10
Sevastjanov P., Kaczmarek K., Rutkowski L., A multi-model approach to the development of algorithmic trading systems for the Forex market. (11)
A multi-model approach to the development of algorithmic trading systems for the Forex market
, A multi-model approach to the development of algorithmic trading systems for the Forex market, Expert Systems with Applications, 236, 236, 2024, Cites: 11
Lin L., Cao J., Lu J., Rutkowski L., Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy. (19)
Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy
, Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy, IEEE Caa Journal of Automatica Sinica, 11, 11, 806-808, 2024, Cites: 19
Urbanczyk A., Kucaba K., Wojtulewicz M., Kisiel-Dorohinicki M., Rutkowski L., Duda P., Kacprzyk J., Yao X., Chong S.Y., Byrski A., (μ +λ) Evolution Strategy with Socio-Cognitive Mutation. (3)
(μ +λ) Evolution Strategy with Socio-Cognitive Mutation
, (μ +λ) Evolution Strategy with Socio-Cognitive Mutation, Journal of Automation Mobile Robotics and Intelligent Systems, 18, 18, 1-11, 2024, Cites: 3
Cheng H., Xiao M., Yu W., Rutkowski L., Cao J., How to regulate pattern formations for malware propagation in cyber-physical systems. (12)
How to regulate pattern formations for malware propagation in cyber-physical systems
, How to regulate pattern formations for malware propagation in cyber-physical systems, Chaos, 34, 34, 2024, Cites: 12
Chen G., Xu G., He F., Hong Y., Rutkowski L., Tao D., Approaching the Global Nash Equilibrium of Non-Convex Multi-Player Games. (7)
Approaching the Global Nash Equilibrium of Non-Convex Multi-Player Games
, Approaching the Global Nash Equilibrium of Non-Convex Multi-Player Games, IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, 46, 10797-10813, 2024, Cites: 7
Dong S., Tang J., Abbas K., Hou R., Kamruzzaman J., Rutkowski L., Buyya R., Task offloading strategies for mobile edge computing: A survey. (118)
Task offloading strategies for mobile edge computing: A survey
, Task offloading strategies for mobile edge computing: A survey, Computer Networks, 254, 254, 2024, Cites: 118
Xin Y., Cheng Z., Cao J., Rutkowski L., Wang Y., Circuit Implementation and Quasi-Stabilization of Delayed Inertial Memristor-Based Neural Networks. (12)
Circuit Implementation and Quasi-Stabilization of Delayed Inertial Memristor-Based Neural Networks
, Circuit Implementation and Quasi-Stabilization of Delayed Inertial Memristor-Based Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, 35, 35, 1394-1400, 2024, Cites: 12
Ju Y., Xiao M., Huang C., Rutkowski L., Cao J., Hybrid control of Turing instability and bifurcation for spatial-temporal propagation of computer virus. (5)
Hybrid control of Turing instability and bifurcation for spatial-temporal propagation of computer virus
, Hybrid control of Turing instability and bifurcation for spatial-temporal propagation of computer virus, International Journal of Systems Science, 55, 55, 2187-2210, 2024, Cites: 5
Wojtulewicz M., Duda P., Nowicki R., Rutkowski L., On Speeding Up the Training of Deep Neural Networks Using the Streaming Approach: The Base-Values Mechanism. (1)
On Speeding Up the Training of Deep Neural Networks Using the Streaming Approach: The Base-Values Mechanism
, On Speeding Up the Training of Deep Neural Networks Using the Streaming Approach: The Base-Values Mechanism, Proceedings of Machine Learning Research, 263, 263, 17-24, 2024, Cites: 1
Kong F., Cao J., Rutkowski L., Zhang Y., Finite-Time Control of Fuzzy Competitive Networks via Comparison Method and Bounded Control. (8)
Finite-Time Control of Fuzzy Competitive Networks via Comparison Method and Bounded Control
, Finite-Time Control of Fuzzy Competitive Networks via Comparison Method and Bounded Control, IEEE Transactions on Fuzzy Systems, 32, 32, 3059-3070, 2024, Cites: 8
Lv X., Cao J., Rutkowski L., Duan P., Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems with Switching Topologies. (28)
Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems with Switching Topologies
, Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems with Switching Topologies, IEEE Transactions on Automatic Control, 69, 69, 771-782, 2024, Cites: 28
Bielaszek S., Rutkowski L., Byrski A., INFLUENCE OF MIGRATION ON EFFICACY AND EFFICIENCY OF PARALLEL EVOLUTIONARY COMPUTING. (0)
INFLUENCE OF MIGRATION ON EFFICACY AND EFFICIENCY OF PARALLEL EVOLUTIONARY COMPUTING
, INFLUENCE OF MIGRATION ON EFFICACY AND EFFICIENCY OF PARALLEL EVOLUTIONARY COMPUTING, Journal of Automation Mobile Robotics and Intelligent Systems, 18, 18, 1-12, 2024, Cites: 0
Rutkowska D., Duda P., Cao J., Jaworski M., Kisiel-Dorohinicki M., Tao D., Rutkowski L., Probabilistic neural networks for incremental learning over time-varying streaming data with application to air pollution monitoring. (4)
Probabilistic neural networks for incremental learning over time-varying streaming data with application to air pollution monitoring
, Probabilistic neural networks for incremental learning over time-varying streaming data with application to air pollution monitoring, Applied Soft Computing, 161, 161, 2024, Cites: 4
Huang Z., Lv W., Liu C., Xu Y., Rutkowski L., Huang T., Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks. (19)
Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks
, Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks, IEEE Transactions on Industrial Informatics, 20, 20, 4218-4226, 2024, Cites: 19
Lin L., Cao J., Lam J., Rutkowski L., Dimirovski G.M., Zhu S., A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains. (21)
A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains
, A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains, IEEE Transactions on Automatic Control, 69, 69, 5743-5758, 2024, Cites: 21
Vovna O., Kaydash H., Rutkowski L., Sakhno I., Laktionov I., Kabanets M., Zozulya S., Computer-Integrated Monitoring Technology with Support-Decision of Unauthorized Disturbance of Methane Sensor Functioning for Coal Mines. (2)
Computer-Integrated Monitoring Technology with Support-Decision of Unauthorized Disturbance of Methane Sensor Functioning for Coal Mines
, Computer-Integrated Monitoring Technology with Support-Decision of Unauthorized Disturbance of Methane Sensor Functioning for Coal Mines, Journal of Control Science and Engineering, 2024, 2024, 2024, Cites: 2
Starzec G., Starzec M., Rutkowski L., Kisiel-Dorohinicki M., Byrski A., Ant colony optimization using two-dimensional pheromone for single-objective transport problems. (10)
Ant colony optimization using two-dimensional pheromone for single-objective transport problems
, Ant colony optimization using two-dimensional pheromone for single-objective transport problems, Journal of Computational Science, 79, 79, 2024, Cites: 10
Ademola A.T., Wen S., Feng Y., Zhang W., Rutkowski L., Stability and boundedness criteria for certain second-order nonlinear neutral stochastic functional differential equations. (0)
Stability and boundedness criteria for certain second-order nonlinear neutral stochastic functional differential equations
, Stability and boundedness criteria for certain second-order nonlinear neutral stochastic functional differential equations, Proyecciones, 43, 43, 985-1009, 2024, Cites: 0
Du X., Xiao M., Luan Y., Ding J., Rutkowski L., Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks. (2)
Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks
, Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks, Journal of Computational and Nonlinear Dynamics, 19, 19, 2024, Cites: 2
Huang X.-X., Xiao M., Rutkowski L., Bao H.-B., Huang X., Cao J.-D., Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks. (1)
Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks
, Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks, Chinese Physics B, 33, 33, 2024, Cites: 1
Lu Y., Yao Y., Huang X., Xiao M., Jiang G., Rutkowski L., Investigation of Spatial Pattern in SI Model with PD Control and Cross-Diffusion. (4)
Investigation of Spatial Pattern in SI Model with PD Control and Cross-Diffusion
, Investigation of Spatial Pattern in SI Model with PD Control and Cross-Diffusion, International Journal of Bifurcation and Chaos, 34, 34, 2024, Cites: 4
He J., Xiao M., He H., Wang Z., Xing Zheng W., Rutkowski L., Facilitating and Determining Turing Patterns in 3-D Memristor Cellular Neural Networks. (8)
Facilitating and Determining Turing Patterns in 3-D Memristor Cellular Neural Networks
, Facilitating and Determining Turing Patterns in 3-D Memristor Cellular Neural Networks, IEEE Transactions on Circuits and Systems I Regular Papers, 71, 71, 4131-4144, 2024, Cites: 8
Li H., Xiao M., Wang Z., Xu F., Wang Z., Zheng W., Rutkowski L., A new chemical networked system: spatial-temporal evolution and control. (2)
A new chemical networked system: spatial-temporal evolution and control
, A new chemical networked system: spatial-temporal evolution and control, Physica Scripta, 99, 99, 2024, Cites: 2
Qi S., Wei W., Wang J., Sun S., Rutkowski L., Huang T., Kacprzyk J., Qi Y., Secure Data Deduplication With Dynamic Access Control for Mobile Cloud Storage. (9)
Secure Data Deduplication With Dynamic Access Control for Mobile Cloud Storage
, Secure Data Deduplication With Dynamic Access Control for Mobile Cloud Storage, IEEE Transactions on Mobile Computing, 23, 23, 2566-2582, 2024, Cites: 9
Duda P., Wojtulewicz M., Rutkowski L., Accelerating deep neural network learning using data stream methodology. (7)
Accelerating deep neural network learning using data stream methodology
, Accelerating deep neural network learning using data stream methodology, Information Sciences, 669, 669, 2024, Cites: 7
Zhou Y., Lv W., Tao J., Xu Y., Huang T., Rutkowski L., Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel. (11)
Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel
, Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel, Neural Networks, 169, 169, 485-495, 2024, Cites: 11
Lin L., Cao J., Lam J., Zhu S., Azuma S.-I., Rutkowski L., Leader-Follower Consensus Over Finite Fields. (21)
Leader-Follower Consensus Over Finite Fields
, Leader-Follower Consensus Over Finite Fields, IEEE Transactions on Automatic Control, 69, 69, 4718-4725, 2024, Cites: 21
Wu J., Cheng J., Yan H., Rutkowski L., Cao J., Observer-Based Sliding Mode Control for Stochastic Sampling Fuzzy Systems with Stochastic Communication Protocol. (11)
Observer-Based Sliding Mode Control for Stochastic Sampling Fuzzy Systems with Stochastic Communication Protocol
, Observer-Based Sliding Mode Control for Stochastic Sampling Fuzzy Systems with Stochastic Communication Protocol, IEEE Transactions on Fuzzy Systems, 32, 32, 7109-7117, 2024, Cites: 11
Cheng H., Xiao M., Lu Y., Bao H., Rutkowski L., Cao J., Complex pattern evolution of a two-dimensional space diffusion model of malware spread. (4)
Complex pattern evolution of a two-dimensional space diffusion model of malware spread
, Complex pattern evolution of a two-dimensional space diffusion model of malware spread, Physica Scripta, 99, 99, 2024, Cites: 42023 (27)
Wu X., Zhu X., Baralis E., Lu R., Kumar V., Rutkowski L., Tang J., On Computing Paradigms - Where Will Large Language Models Be Going. (1)
On Computing Paradigms - Where Will Large Language Models Be Going
, On Computing Paradigms - Where Will Large Language Models Be Going, Proceedings IEEE International Conference on Data Mining Icdm, 1577-1582, 2023, Cites: 1
Chen B., Cao J., Lu G., Rutkowski L., Stabilization of Markovian Jump Boolean Control Networks via Event-Triggered Control. (30)
Stabilization of Markovian Jump Boolean Control Networks via Event-Triggered Control
, Stabilization of Markovian Jump Boolean Control Networks via Event-Triggered Control, IEEE Transactions on Automatic Control, 68, 68, 1215-1222, 2023, Cites: 30
Wang J., Wu J., Shen H., Cao J., Rutkowski L., Fuzzy H∞ Control of Discrete-Time Nonlinear Markov Jump Systems via a Novel Hybrid Reinforcement Q-Learning Method. (247)
Fuzzy H∞ Control of Discrete-Time Nonlinear Markov Jump Systems via a Novel Hybrid Reinforcement Q-Learning Method
, Fuzzy H∞ Control of Discrete-Time Nonlinear Markov Jump Systems via a Novel Hybrid Reinforcement Q-Learning Method, IEEE Transactions on Cybernetics, 53, 53, 7380-7391, 2023, Cites: 247
Wang J., Chen Z., Shen H., Cao J., Rutkowski L., Fuzzy H∞ Control of Semi-Markov Jump Singularly Perturbed Nonlinear Systems With Partial Information and Actuator Saturation. (12)
Fuzzy H∞ Control of Semi-Markov Jump Singularly Perturbed Nonlinear Systems With Partial Information and Actuator Saturation
, Fuzzy H∞ Control of Semi-Markov Jump Singularly Perturbed Nonlinear Systems With Partial Information and Actuator Saturation, IEEE Transactions on Fuzzy Systems, 31, 31, 4374-4384, 2023, Cites: 12
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 14125 LNAI, 14125 LNAI, v-vi, 2023, Cites: 0
Krokosz T., Rykowski J., Zajecka M., Brzoza-Woch R., Rutkowski L., Cryptographic Algorithms with Data Shorter than the Encryption Key, Based on LZW and Huffman Coding. (6)
Cryptographic Algorithms with Data Shorter than the Encryption Key, Based on LZW and Huffman Coding
, Cryptographic Algorithms with Data Shorter than the Encryption Key, Based on LZW and Huffman Coding, Sensors, 23, 23, 2023, Cites: 6
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 14126 LNAI, 14126 LNAI, v-vi, 2023, Cites: 0
Duda P., Wojtulewicz M., Rutkowski L., The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach. (0)
The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach
, The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 14125 LNAI, 14125 LNAI, 46-55, 2023, Cites: 0
Zhu W., Cao J., Shi X., Rutkowski L., Leader-following consensus of finite-field networks with time-delays. (5)
Leader-following consensus of finite-field networks with time-delays
, Leader-following consensus of finite-field networks with time-delays, Information Sciences, 647, 647, 2023, Cites: 5
Sevastjanov P., Kaczmarek K., Rutkowski L., A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization. (7)
A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization
, A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization, Applied Soft Computing, 147, 147, 2023, Cites: 7
Laktionov I., Rutkowski L., Vovna O., Byrski A., Kabanets M., A novel approach to intelligent monitoring of gas composition and light mode of greenhouse crop growing zone on the basis of fuzzy modelling and human-in-the-loop techniques. (11)
A novel approach to intelligent monitoring of gas composition and light mode of greenhouse crop growing zone on the basis of fuzzy modelling and human-in-the-loop techniques
, A novel approach to intelligent monitoring of gas composition and light mode of greenhouse crop growing zone on the basis of fuzzy modelling and human-in-the-loop techniques, Engineering Applications of Artificial Intelligence, 126, 126, 2023, Cites: 11
Lin A., Cheng J., Rutkowski L., Wen S., Luo M., Cao J., Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol. (30)
Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol
, Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol, IEEE Transactions on Neural Networks and Learning Systems, 34, 34, 9004-9015, 2023, Cites: 30
Starzec G., Starzec M., Bandyopadhyay S., Maulik U., Rutkowski L., Kisiel-Dorohinicki M., Byrski A., Two-Dimensional Pheromone in Ant Colony Optimization. (2)
Two-Dimensional Pheromone in Ant Colony Optimization
, Two-Dimensional Pheromone in Ant Colony Optimization, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 14162 LNAI, 14162 LNAI, 459-471, 2023, Cites: 2
Zhu S., Cao J., Lin L., Rutkowski L., Lu J., Lu G., Observability and Detectability of Stochastic Labeled Graphs. (33)
Observability and Detectability of Stochastic Labeled Graphs
, Observability and Detectability of Stochastic Labeled Graphs, IEEE Transactions on Automatic Control, 68, 68, 7299-7311, 2023, Cites: 33
Izonin I., Tkachenko R., Gurbych O., Kovac M., Rutkowski L., Holoven R., A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis. (7)
A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis
, A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis, Mathematical Biosciences and Engineering, 20, 20, 13398-13414, 2023, Cites: 7
Urbanczyk A., Kipinski P., Nabywaniec M., Rutkowski L., Chong S.Y., Yao X., Boryczko K., Byrski A., Socio-cognitive caste-based optimization. (0)
Socio-cognitive caste-based optimization
, Socio-cognitive caste-based optimization, Journal of Computational Science, 72, 72, 2023, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 13588 LNAI, 13588 LNAI, v-vi, 2023, Cites: 0
Zhang N., Wang J., Rutkowski L., Special issue on deep interpretation of deep learning: prediction, representation, modeling and utilization. (1)
Special issue on deep interpretation of deep learning: prediction, representation, modeling and utilization
, Special issue on deep interpretation of deep learning: prediction, representation, modeling and utilization, Neural Computing and Applications, 35, 35, 9947-9949, 2023, Cites: 1
Cheng J., Wu F., Liu L., Zhang Q., Rutkowski L., Tao D., InDecGAN: Learning to Generate Complex Images from Captions via Independent Object-Level Decomposition and Enhancement. (3)
InDecGAN: Learning to Generate Complex Images from Captions via Independent Object-Level Decomposition and Enhancement
, InDecGAN: Learning to Generate Complex Images from Captions via Independent Object-Level Decomposition and Enhancement, IEEE Transactions on Multimedia, 25, 25, 8279-8293, 2023, Cites: 3
Wang J., Wu J., Shen H., Cao J., Rutkowski L., A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism. (27)
A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism
, A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism, IEEE Transactions on Systems Man and Cybernetics Systems, 53, 53, 4934-4943, 2023, Cites: 27
Guan H., Liu Y., Kou K.I., Cao J., Rutkowski L., Collaborative neurodynamic optimization for solving nonlinear equations. (9)
Collaborative neurodynamic optimization for solving nonlinear equations
, Collaborative neurodynamic optimization for solving nonlinear equations, Neural Networks, 165, 165, 483-490, 2023, Cites: 9
Shen H., Zhang Y., Wang J., Cao J., Rutkowski L., Observer-Based Control for Discrete-Time Hidden Semi-Markov Jump Systems. (29)
Observer-Based Control for Discrete-Time Hidden Semi-Markov Jump Systems
, Observer-Based Control for Discrete-Time Hidden Semi-Markov Jump Systems, IEEE Transactions on Automatic Control, 68, 68, 6255-6261, 2023, Cites: 29
Wang Y., Yan J., Huang W., Rutkowski L., Cao J., Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track. (9)
Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track
, Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track, Science China Information Sciences, 66, 66, 2023, Cites: 9
Feng Z.C., Xu W.Y., Cao J.D., Yang S.F., Rutkowski L., Distributed online bandit tracking for Nash equilibrium under partial-decision information setting. (1)
Distributed online bandit tracking for Nash equilibrium under partial-decision information setting
, Distributed online bandit tracking for Nash equilibrium under partial-decision information setting, Science China Technological Sciences, 66, 66, 3129-3138, 2023, Cites: 1
Ghaffari R., Helfroush M.S., Khosravi A., Kazemi K., Danyali H., Rutkowski L., Toward domain adaptation with open-set target data: Review of theory and computer vision applications. (23)
Toward domain adaptation with open-set target data: Review of theory and computer vision applications
, Toward domain adaptation with open-set target data: Review of theory and computer vision applications, Information Fusion, 100, 100, 2023, Cites: 23
Rutkowska D., Duda P., Cao J., Rutkowski L., Byrski A., Jaworski M., Tao D., The L2 convergence of stream data mining algorithms based on probabilistic neural networks. (7)
The L2 convergence of stream data mining algorithms based on probabilistic neural networks
, The L2 convergence of stream data mining algorithms based on probabilistic neural networks, Information Sciences, 631, 631, 346-368, 2023, Cites: 7
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 13589 LNAI, 13589 LNAI, v-vi, 2023, Cites: 02022 (16)
Yu T., Cao J., Rutkowski L., Luo Y.-P., Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control. (77)
Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control
, Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control, IEEE Transactions on Neural Networks and Learning Systems, 33, 33, 3938-3947, 2022, Cites: 77
Zhu W., Cao J., Shi X., Rutkowski L., Synchronization of Finite-Field Networks With Time Delays. (15)
Synchronization of Finite-Field Networks With Time Delays
, Synchronization of Finite-Field Networks With Time Delays, IEEE Transactions on Network Science and Engineering, 9, 9, 347-355, 2022, Cites: 15
Hu J., Cao J., Rutkowski L., Xue C., Yu J., Hierarchical interactive demand response power profile tracking optimization and control of multiple EV aggregators. (15)
Hierarchical interactive demand response power profile tracking optimization and control of multiple EV aggregators
, Hierarchical interactive demand response power profile tracking optimization and control of multiple EV aggregators, Electric Power Systems Research, 208, 208, 2022, Cites: 15
Shen H., Wang X., Wang J., Cao J., Rutkowski L., Robust Composite H∞Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method. (33)
Robust Composite H∞Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method
, Robust Composite H∞Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method, IEEE Transactions on Cybernetics, 52, 52, 12712-12721, 2022, Cites: 33
Feng Y., Zhang W., Xiong J., Li H., Rutkowski L., Event-Triggering Interaction Scheme for Discrete-Time Decentralized Optimization with Nonuniform Step Sizes. (20)
Event-Triggering Interaction Scheme for Discrete-Time Decentralized Optimization with Nonuniform Step Sizes
, Event-Triggering Interaction Scheme for Discrete-Time Decentralized Optimization with Nonuniform Step Sizes, IEEE Transactions on Cybernetics, 52, 52, 748-757, 2022, Cites: 20
Tan X., Xiang C., Cao J., Xu W., Wen G., Rutkowski L., Synchronization of Neural Networks via Periodic Self-Triggered Impulsive Control and Its Application in Image Encryption. (103)
Synchronization of Neural Networks via Periodic Self-Triggered Impulsive Control and Its Application in Image Encryption
, Synchronization of Neural Networks via Periodic Self-Triggered Impulsive Control and Its Application in Image Encryption, IEEE Transactions on Cybernetics, 52, 52, 8246-8257, 2022, Cites: 103
Grycuk R., Galkowski T., Scherer R., Rutkowski L., A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder. (9)
A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder
, A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder, Proceedings of the International Joint Conference on Neural Networks, 2022, Cites: 9
Song Y., Cao J., Rutkowski L., A Fixed-Time Distributed Optimization Algorithm Based on Event-Triggered Strategy. (93)
A Fixed-Time Distributed Optimization Algorithm Based on Event-Triggered Strategy
, A Fixed-Time Distributed Optimization Algorithm Based on Event-Triggered Strategy, IEEE Transactions on Network Science and Engineering, 9, 9, 1154-1162, 2022, Cites: 93
Li H., Fang J.-A., Li X., Rutkowski L., Huang T., Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays. (32)
Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays
, Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays, IEEE Transactions on Circuits and Systems I Regular Papers, 69, 69, 2095-2107, 2022, Cites: 32
Feng L., Liu L., Cao J., Rutkowski L., Lu G., General Decay Stability for Nonautonomous Neutral Stochastic Systems with Time-Varying Delays and Markovian Switching. (18)
General Decay Stability for Nonautonomous Neutral Stochastic Systems with Time-Varying Delays and Markovian Switching
, General Decay Stability for Nonautonomous Neutral Stochastic Systems with Time-Varying Delays and Markovian Switching, IEEE Transactions on Cybernetics, 52, 52, 5441-5453, 2022, Cites: 18
Staszewski P., Jaworski M., Cao J., Rutkowski L., A New Approach to Descriptors Generation for Image Retrieval by Analyzing Activations of Deep Neural Network Layers. (30)
A New Approach to Descriptors Generation for Image Retrieval by Analyzing Activations of Deep Neural Network Layers
, A New Approach to Descriptors Generation for Image Retrieval by Analyzing Activations of Deep Neural Network Layers, IEEE Transactions on Neural Networks and Learning Systems, 33, 33, 7913-7920, 2022, Cites: 30
Godzik M., Dajda J., Kisiel-Dorohinicki M., Byrski A., Rutkowski L., Orzechowski P., Wagenaar J., Moore J.H., Applying autonomous hybrid agent-based computing to difficult optimization problems. (1)
Applying autonomous hybrid agent-based computing to difficult optimization problems
, Applying autonomous hybrid agent-based computing to difficult optimization problems, Journal of Computational Science, 64, 64, 2022, Cites: 1
Zhang N., Wang J., Rutkowski L., Editorial: Special Issue on Reliable Machine Learning and Optimization. (0)
Editorial: Special Issue on Reliable Machine Learning and Optimization
, Editorial: Special Issue on Reliable Machine Learning and Optimization, International Journal on Artificial Intelligence Tools, 31, 31, 2022, Cites: 0
Li Z., Tang Y., Fan Y., Huang T., Rutkowski L., Formation Control of Multi-Agent Systems With Constrained Mismatched Compasses. (12)
Formation Control of Multi-Agent Systems With Constrained Mismatched Compasses
, Formation Control of Multi-Agent Systems With Constrained Mismatched Compasses, IEEE Transactions on Network Science and Engineering, 9, 9, 2224-2236, 2022, Cites: 12
Chen B., Cao J., Lu G., Rutkowski L., Stabilization of Markovian Jump Boolean Control Networks via Sampled-Data Control. (22)
Stabilization of Markovian Jump Boolean Control Networks via Sampled-Data Control
, Stabilization of Markovian Jump Boolean Control Networks via Sampled-Data Control, IEEE Transactions on Cybernetics, 52, 52, 10290-10301, 2022, Cites: 22
Luo Y., Zhu W., Cao J., Rutkowski L., Event-Triggered Finite-Time Guaranteed Cost H-Infinity Consensus for Nonlinear Uncertain Multi-Agent Systems. (62)
Event-Triggered Finite-Time Guaranteed Cost H-Infinity Consensus for Nonlinear Uncertain Multi-Agent Systems
, Event-Triggered Finite-Time Guaranteed Cost H-Infinity Consensus for Nonlinear Uncertain Multi-Agent Systems, IEEE Transactions on Network Science and Engineering, 9, 9, 1527-1539, 2022, Cites: 622021 (13)
Bilski J., Rutkowski L., Smolag J., Tao D., A novel method for speed training acceleration of recurrent neural networks. (24)
A novel method for speed training acceleration of recurrent neural networks
, A novel method for speed training acceleration of recurrent neural networks, Information Sciences, 553, 553, 266-279, 2021, Cites: 24
Xu S., Cao J., Liu Q., Rutkowski L., Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System with Heuristic Method. (18)
Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System with Heuristic Method
, Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System with Heuristic Method, IEEE Transactions on Systems Man and Cybernetics Systems, 51, 51, 3617-3628, 2021, Cites: 18
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12855 LNAI, 12855 LNAI, v-vi, 2021, Cites: 0
Yang X., Wan X., Zunshui C., Cao J., Liu Y., Rutkowski L., Synchronization of Switched Discrete-Time Neural Networks via Quantized Output Control with Actuator Fault. (134)
Synchronization of Switched Discrete-Time Neural Networks via Quantized Output Control with Actuator Fault
, Synchronization of Switched Discrete-Time Neural Networks via Quantized Output Control with Actuator Fault, IEEE Transactions on Neural Networks and Learning Systems, 32, 32, 4191-4201, 2021, Cites: 134
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12854 LNAI, 12854 LNAI, v-vi, 2021, Cites: 0
Duda P., Rutkowski L., Woldan P., Najgebauer P., The Streaming Approach to Training Restricted Boltzmann Machines. (0)
The Streaming Approach to Training Restricted Boltzmann Machines
, The Streaming Approach to Training Restricted Boltzmann Machines, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12854 LNAI, 12854 LNAI, 308-317, 2021, Cites: 0
Jaworski M., Rutkowski L., Staszewski P., Najgebauer P., Monitoring of Changes in Data Stream Distribution Using Convolutional Restricted Boltzmann Machines. (2)
Monitoring of Changes in Data Stream Distribution Using Convolutional Restricted Boltzmann Machines
, Monitoring of Changes in Data Stream Distribution Using Convolutional Restricted Boltzmann Machines, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12854 LNAI, 12854 LNAI, 338-346, 2021, Cites: 2
Lv X., Cao J., Rutkowski L., Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control. (21)
Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control
, Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control, Neural Networks, 143, 143, 515-524, 2021, Cites: 21
Tan X., Cao J., Rutkowski L., Lu G., Distributed Dynamic Self-Triggered Impulsive Control for Consensus Networks: The Case of Impulse Gain with Normal Distribution. (52)
Distributed Dynamic Self-Triggered Impulsive Control for Consensus Networks: The Case of Impulse Gain with Normal Distribution
, Distributed Dynamic Self-Triggered Impulsive Control for Consensus Networks: The Case of Impulse Gain with Normal Distribution, IEEE Transactions on Cybernetics, 51, 51, 624-634, 2021, Cites: 52
Xiong H., Tang Y.Y., Murtagh F., Rutkowski L., Berkovsky S., A diversified shared latent variable model for efficient image characteristics extraction and modelling. (5)
A diversified shared latent variable model for efficient image characteristics extraction and modelling
, A diversified shared latent variable model for efficient image characteristics extraction and modelling, Neurocomputing, 421, 421, 244-259, 2021, Cites: 5
Xia Z., Liu Y., Lu J., Cao J., Rutkowski L., Penalty method for constrained distributed quaternion-variable optimization. (65)
Penalty method for constrained distributed quaternion-variable optimization
, Penalty method for constrained distributed quaternion-variable optimization, IEEE Transactions on Cybernetics, 51, 51, 5631-5636, 2021, Cites: 65
He J., Liu Y., Lu J., Cao J., Rutkowski L., Event-Triggered Control for Output Regulation of Probabilistic Logical Systems with Delays. (9)
Event-Triggered Control for Output Regulation of Probabilistic Logical Systems with Delays
, Event-Triggered Control for Output Regulation of Probabilistic Logical Systems with Delays, IEEE Transactions on Systems Man and Cybernetics Systems, 51, 51, 6842-6851, 2021, Cites: 9
Wang J., Yang C., Shen H., Cao J., Rutkowski L., Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters. (134)
Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters
, Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters, IEEE Transactions on Systems Man and Cybernetics Systems, 51, 51, 7579-7586, 2021, Cites: 1342020 (32)
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12416 LNAI, 12416 LNAI, v-vi, 2020, Cites: 0
Rutkowski T., Nielek R., Rutkowska D., Rutkowski L., A Novel Explainable Recommender for Investment Managers. (2)
A Novel Explainable Recommender for Investment Managers
, A Novel Explainable Recommender for Investment Managers, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12416 LNAI, 12416 LNAI, 412-422, 2020, Cites: 2
Tan X., Cao J., Rutkowski L., Distributed Dynamic Self-Triggered Control for Uncertain Complex Networks with Markov Switching Topologies and Random Time-Varying Delay. (89)
Distributed Dynamic Self-Triggered Control for Uncertain Complex Networks with Markov Switching Topologies and Random Time-Varying Delay
, Distributed Dynamic Self-Triggered Control for Uncertain Complex Networks with Markov Switching Topologies and Random Time-Varying Delay, IEEE Transactions on Network Science and Engineering, 7, 7, 1111-1120, 2020, Cites: 89
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Data Stream Mining. (20)
Basic Concepts of Data Stream Mining
, Basic Concepts of Data Stream Mining, Studies in Big Data, 56, 56, 13-33, 2020, Cites: 20
Duda P., Rutkowski L., Jaworski M., Rutkowska D., On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification. (35)
On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification
, On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification, IEEE Transactions on Cybernetics, 50, 50, 1683-1696, 2020, Cites: 35
Rutkowski L., Jaworski M., Duda P., Splitting Criteria with the Bias Term. (1)
Splitting Criteria with the Bias Term
, Splitting Criteria with the Bias Term, Studies in Big Data, 56, 56, 83-89, 2020, Cites: 1
Jaworski M., Rutkowski L., Angelov P., Concept Drift Detection Using Autoencoders in Data Streams Processing. (24)
Concept Drift Detection Using Autoencoders in Data Streams Processing
, Concept Drift Detection Using Autoencoders in Data Streams Processing, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12415 LNAI, 12415 LNAI, 124-133, 2020, Cites: 24
Rutkowski L., Jaworski M., Duda P., Classification. (0)
Classification
, Classification, Studies in Big Data, 56, 56, 287-308, 2020, Cites: 0
Rutkowski L., Jaworski M., Duda P., Misclassification Error Impurity Measure. (2)
Misclassification Error Impurity Measure
, Misclassification Error Impurity Measure, Studies in Big Data, 56, 56, 63-82, 2020, Cites: 2
Yang X., Liu Y., Cao J., Rutkowski L., Synchronization of Coupled Time-Delay Neural Networks with Mode-Dependent Average Dwell Time Switching. (143)
Synchronization of Coupled Time-Delay Neural Networks with Mode-Dependent Average Dwell Time Switching
, Synchronization of Coupled Time-Delay Neural Networks with Mode-Dependent Average Dwell Time Switching, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 5483-5496, 2020, Cites: 143
Rutkowski L., Jaworski M., Duda P., The General Procedure of Ensembles Construction in Data Stream Scenarios. (0)
The General Procedure of Ensembles Construction in Data Stream Scenarios
, The General Procedure of Ensembles Construction in Data Stream Scenarios, Studies in Big Data, 56, 56, 281-286, 2020, Cites: 0
Wang Z., Cao J., Cai Z., Rutkowski L., Anti-synchronization in fixed time for discontinuous reaction-diffusion neural networks with time-varying coefficients and time delay. (82)
Anti-synchronization in fixed time for discontinuous reaction-diffusion neural networks with time-varying coefficients and time delay
, Anti-synchronization in fixed time for discontinuous reaction-diffusion neural networks with time-varying coefficients and time delay, IEEE Transactions on Cybernetics, 50, 50, 2758-2769, 2020, Cites: 82
Rutkowski L., Jaworski M., Duda P., Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks. (1)
Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks
, Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks, Studies in Big Data, 56, 56, 173-244, 2020, Cites: 1
Rutkowski L., Jaworski M., Duda P., Introduction and Overview of the Main Results of the Book. (1)
Introduction and Overview of the Main Results of the Book
, Introduction and Overview of the Main Results of the Book, Studies in Big Data, 56, 56, 1-10, 2020, Cites: 1
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12415 LNAI, 12415 LNAI, v-vi, 2020, Cites: 0
Rutkowski L., Jaworski M., Duda P., Regression. (0)
Regression
, Regression, Studies in Big Data, 56, 56, 309-322, 2020, Cites: 0
Liu Y., Zheng Y., Lu J., Cao J., Rutkowski L., Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach. (109)
Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach
, Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 1022-1035, 2020, Cites: 109
Chen B., Cao J., Luo Y., Rutkowski L., Asymptotic Output Tracking of Probabilistic Boolean Control Networks. (56)
Asymptotic Output Tracking of Probabilistic Boolean Control Networks
, Asymptotic Output Tracking of Probabilistic Boolean Control Networks, IEEE Transactions on Circuits and Systems I Regular Papers, 67, 67, 2780-2790, 2020, Cites: 56
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Probabilistic Neural Networks. (0)
Basic Concepts of Probabilistic Neural Networks
, Basic Concepts of Probabilistic Neural Networks, Studies in Big Data, 56, 56, 117-154, 2020, Cites: 0
Rutkowski L., Jaworski M., Duda P., Decision Trees in Data Stream Mining. (11)
Decision Trees in Data Stream Mining
, Decision Trees in Data Stream Mining, Studies in Big Data, 56, 56, 37-50, 2020, Cites: 11
Rutkowski L., Jaworski M., Duda P., Splitting Criteria Based on the McDiarmid’s Theorem. (0)
Splitting Criteria Based on the McDiarmid’s Theorem
, Splitting Criteria Based on the McDiarmid’s Theorem, Studies in Big Data, 56, 56, 51-62, 2020, Cites: 0
Staszewski P., Jaworski M., Rutkowski L., Tao D., Explainable Cluster-Based Rules Generation for Image Retrieval and Classification. (1)
Explainable Cluster-Based Rules Generation for Image Retrieval and Classification
, Explainable Cluster-Based Rules Generation for Image Retrieval and Classification, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12416 LNAI, 12416 LNAI, 85-94, 2020, Cites: 1
Rutkowski L., Jaworski M., Duda P., General Non-parametric Learning Procedure for Tracking Concept Drift. (2)
General Non-parametric Learning Procedure for Tracking Concept Drift
, General Non-parametric Learning Procedure for Tracking Concept Drift, Studies in Big Data, 56, 56, 155-172, 2020, Cites: 2
Rutkowski L., Jaworski M., Duda P., Probabilistic Neural Networks for the Streaming Data Classification. (4)
Probabilistic Neural Networks for the Streaming Data Classification
, Probabilistic Neural Networks for the Streaming Data Classification, Studies in Big Data, 56, 56, 245-277, 2020, Cites: 4
Rutkowski L., Jaworski M., Duda P., Final Remarks and Challenging Problems. (0)
Final Remarks and Challenging Problems
, Final Remarks and Challenging Problems, Studies in Big Data, 56, 56, 323-327, 2020, Cites: 0
Najgebauer P., Scherer R., Rutkowski L., Fully Convolutional Network for Removing DCT Artefacts from Images. (8)
Fully Convolutional Network for Removing DCT Artefacts from Images
, Fully Convolutional Network for Removing DCT Artefacts from Images, Proceedings of the International Joint Conference on Neural Networks, 2020, Cites: 8
Chen B., Cao J., Lu G., Rutkowski L., Lyapunov Functions for the Set Stability and the Synchronization of Boolean Control Networks. (36)
Lyapunov Functions for the Set Stability and the Synchronization of Boolean Control Networks
, Lyapunov Functions for the Set Stability and the Synchronization of Boolean Control Networks, IEEE Transactions on Circuits and Systems II Express Briefs, 67, 67, 2537-2541, 2020, Cites: 36
Cao J.-D., Liu Y., Lu J.-Q., Rutkowski L., Complex systems and networks with their applications. (3)
Complex systems and networks with their applications
, Complex systems and networks with their applications, Frontiers of Information Technology and Electronic Engineering, 21, 21, 195-198, 2020, Cites: 3
Lin L., Cao J., Rutkowski L., Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks. (55)
Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks
, Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 1060-1065, 2020, Cites: 55
Li H., Fang J.-A., Li X., Rutkowski L., Huang T., Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays. (24)
Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays
, Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays, Neural Networks, 132, 132, 447-460, 2020, Cites: 24
Lin L., Cao J., Zhu S., Rutkowski L., Lu G., Sampled-Data Set Stabilization of Impulsive Boolean Networks Based on a Hybrid Index Model. (39)
Sampled-Data Set Stabilization of Impulsive Boolean Networks Based on a Hybrid Index Model
, Sampled-Data Set Stabilization of Impulsive Boolean Networks Based on a Hybrid Index Model, IEEE Transactions on Control of Network Systems, 7, 7, 1859-1869, 2020, Cites: 39
Rutkowski L., Jaworski M., Duda P., Hybrid Splitting Criteria. (1)
Hybrid Splitting Criteria
, Hybrid Splitting Criteria, Studies in Big Data, 56, 56, 91-113, 2020, Cites: 12019 (9)
Jaworski M., Duda P., Rutkowska D., Rutkowski L., On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine. (3)
On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine
, On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine, Communications in Computer and Information Science, 1143 CCIS, 1143 CCIS, 347-354, 2019, Cites: 3
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028)). (0)
Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028))
, Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028)), Information Sciences, 477, 477, 545, 2019, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11509 LNAI, 11509 LNAI, v-vi, 2019, Cites: 0
Rutkowska D., Rutkowski L., On the hermite series-based generalized regression neural networks for stream data mining. (1)
On the hermite series-based generalized regression neural networks for stream data mining
, On the hermite series-based generalized regression neural networks for stream data mining, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11955 LNCS, 11955 LNCS, 437-448, 2019, Cites: 1
Najgebauer P., Grycuk R., Rutkowski L., Scherer R., Siwocha A., Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection. (9)
Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection
, Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11508 LNAI, 11508 LNAI, 164-171, 2019, Cites: 9
Feng L., Cao J., Hu J., Wu Z., Rutkowski L., Exponential Stabilization for Hybrid Recurrent Neural Networks by Delayed Noises Rooted in Discrete Observations of State and Mode. (3)
Exponential Stabilization for Hybrid Recurrent Neural Networks by Delayed Noises Rooted in Discrete Observations of State and Mode
, Exponential Stabilization for Hybrid Recurrent Neural Networks by Delayed Noises Rooted in Discrete Observations of State and Mode, Neural Processing Letters, 50, 50, 2797-2819, 2019, Cites: 3
Jaworski M., Rutkowski L., Duda P., Cader A., Resource-aware data stream mining using the restricted boltzmann machine. (4)
Resource-aware data stream mining using the restricted boltzmann machine
, Resource-aware data stream mining using the restricted boltzmann machine, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11509 LNAI, 11509 LNAI, 384-396, 2019, Cites: 4
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11508 LNAI, 11508 LNAI, v-vi, 2019, Cites: 0
Woldan P., Staszewski P., Rutkowski L., Grzanek K., On Proper Designing of Deep Structures for Image Classification. (0)
On Proper Designing of Deep Structures for Image Classification
, On Proper Designing of Deep Structures for Image Classification, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11508 LNAI, 11508 LNAI, 223-235, 2019, Cites: 02018 (11)
Jaworski M., Duda P., Rutkowski L., New Splitting Criteria for Decision Trees in Stationary Data Streams. (98)
New Splitting Criteria for Decision Trees in Stationary Data Streams
, New Splitting Criteria for Decision Trees in Stationary Data Streams, IEEE Transactions on Neural Networks and Learning Systems, 29, 29, 2516-2529, 2018, Cites: 98
Duda P., Jaworski M., Rutkowski L., Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks. (31)
Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks
, Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks, International Journal of Neural Systems, 28, 28, 2018, Cites: 31
Zalasinski M., Cpalka K., Rutkowski L., Fuzzy-genetic approach to identity verification using a handwritten signature. (6)
Fuzzy-genetic approach to identity verification using a handwritten signature
, Fuzzy-genetic approach to identity verification using a handwritten signature, Studies in Computational Intelligence, 738, 738, 375-394, 2018, Cites: 6
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10841 LNAI, 10841 LNAI, V-VI, 2018, Cites: 0
Rutkowski T., Romanowski J., Woldan P., Staszewski P., Nielek R., Rutkowski L., A content-based recommendation system using neuro-fuzzy approach. (55)
A content-based recommendation system using neuro-fuzzy approach
, A content-based recommendation system using neuro-fuzzy approach, IEEE International Conference on Fuzzy Systems, 2018-July, 2018-July, 2018, Cites: 55
Jaworski M., Duda P., Rutkowski L., Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine. (14)
Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine
, Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine, Proceedings of the International Joint Conference on Neural Networks, 2018-July, 2018-July, 2018, Cites: 14
Duda P., Jaworski M., Rutkowski L., Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks. (25)
Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks
, Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks, Information Sciences, 460-461, 460-461, 497-518, 2018, Cites: 25
Duda P., Jaworski M., Rutkowski L., Online grnn-based ensembles for regression on evolving data streams. (6)
Online grnn-based ensembles for regression on evolving data streams
, Online grnn-based ensembles for regression on evolving data streams, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10878 LNCS, 10878 LNCS, 221-228, 2018, Cites: 6
Lapa K., Cpalka K., Rutkowski L., New aspects of interpretability of fuzzy systems for nonlinear modeling. (16)
New aspects of interpretability of fuzzy systems for nonlinear modeling
, New aspects of interpretability of fuzzy systems for nonlinear modeling, Studies in Computational Intelligence, 738, 738, 225-264, 2018, Cites: 16
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10842 LNAI, 10842 LNAI, V-VI, 2018, Cites: 0
Cao J., Rutkowski L., On the global convergence of the parzen-based generalized regression neural networks applied to streaming data. (1)
On the global convergence of the parzen-based generalized regression neural networks applied to streaming data
, On the global convergence of the parzen-based generalized regression neural networks applied to streaming data, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10841 LNAI, 10841 LNAI, 25-34, 2018, Cites: 12017 (8)
Najgebauer P., Rutkowski L., Scherer R., Interest point localization based on edge detection according to gestalt laws. (2)
Interest point localization based on edge detection according to gestalt laws
, Interest point localization based on edge detection according to gestalt laws, 2017 2nd IEEE International Conference on Computational Intelligence and Applications Iccia 2017, 2017-January, 2017-January, 349-353, 2017, Cites: 2
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10246 LNAI, 10246 LNAI, V-VI, 2017, Cites: 0
Rutkowski L., Preface. (0)
Preface
, Preface, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10245 LNAI, 10245 LNAI, v-vi, 2017, Cites: 0
Duda P., Jaworski M., Rutkowski L., On ensemble components selection in data streams scenario with reoccurring concept-drift. (16)
On ensemble components selection in data streams scenario with reoccurring concept-drift
, On ensemble components selection in data streams scenario with reoccurring concept-drift, 2017 IEEE Symposium Series on Computational Intelligence Ssci 2017 Proceedings, 2018-January, 2018-January, 1-7, 2017, Cites: 16
Jaworski M., Duda P., Rutkowski L., On applying the Restricted Boltzmann Machine to active concept drift detection. (24)
On applying the Restricted Boltzmann Machine to active concept drift detection
, On applying the Restricted Boltzmann Machine to active concept drift detection, 2017 IEEE Symposium Series on Computational Intelligence Ssci 2017 Proceedings, 2018-January, 2018-January, 1-8, 2017, Cites: 24
Najgebauer P., Rutkowski L., Scherer R., Novel method for joining missing line fragments for medical image analysis. (3)
Novel method for joining missing line fragments for medical image analysis
, Novel method for joining missing line fragments for medical image analysis, 2017 22nd International Conference on Methods and Models in Automation and Robotics Mmar 2017, 861-866, 2017, Cites: 3
Jaworski M., Duda P., Rutkowski L., Najgebauer P., Pawlak M., Heuristic regression function estimation methods for data streams with concept drift. (10)
Heuristic regression function estimation methods for data streams with concept drift
, Heuristic regression function estimation methods for data streams with concept drift, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10246 LNAI, 10246 LNAI, 726-737, 2017, Cites: 10
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., How to adjust an ensemble size in stream data mining?. (67)
How to adjust an ensemble size in stream data mining?
, How to adjust an ensemble size in stream data mining?, Information Sciences, 381, 381, 46-54, 2017, Cites: 672016 (1)
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., A method for automatic adjustment of ensemble size in stream data mining. (18)
