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Position:
Full Professor

Classes:
Seminarium kierunkowe
Sem. dyplomowe i przygotowanie pracy dyplomowej
Foundations of computer network lec.
Systemy rozmyte i przetwarzanie niepewności lab.
Metody sztucznej inteligencji
Systemy rozmyte i przetwarzanie niepewności wyk.
Bezpieczeństwo komunikacji elektronicznej wyk.
Prof. PhD DSc Eng Robert Nowicki

Papers (101)

2020 (1)

Rough support vector machine for classification with interval and incomplete data
Robert K Nowicki and Konrad Grzanek and Yoichi Hayashi, Rough support vector machine for classification with interval and incomplete data, 2020, Cites: 3

2019 (11)

Rough Fuzzy Classification Systems
Robert K Nowicki, Rough Fuzzy Classification Systems, Springer, Cham, 17-70, 2019, Cites: 0
Fuzzy Rough Classification Systems
Robert K Nowicki, Fuzzy Rough Classification Systems, Springer, Cham, 71-93, 2019, Cites: 0
Rough set theory fundamentals
Robert K Nowicki, Rough set theory fundamentals, Springer, Cham, 7-16, 2019, Cites: 2
Rough Neural Network Classifier
Robert K Nowicki, Rough Neural Network Classifier, Springer, Cham, 95-132, 2019, Cites: 1
Sequential Data Mining of Network Traffic in URL Logs
Marcin Korytkowski and Jakub Nowak and Robert Nowicki and Kamila Milkowska and Magdalena Scherer and Piotr Goetzen, Sequential Data Mining of Network Traffic in URL Logs, Springer, Cham, 125-130, 2019, Cites: 1
Multilayer Architecture for Content-based Image Retrieval Systems
Rafal Grycuk and Patryk Najgebauer and Robert Nowicki and Rafal Scherer, Multilayer Architecture for Content-based Image Retrieval Systems, IEEE, 119-126, 2019, Cites: 1
Fuzzy-rough Fuzzification in General FL Classifiers.
Janusz T Starczewski and Robert K Nowicki and Katarzyna Nieszporek, Fuzzy-rough Fuzzification in General FL Classifiers., 335-342, 2019, Cites: 1
On explainable recommender systems based on fuzzy rule generation techniques
Tomasz Rutkowski and Krystian Łapa and Robert Nowicki and Radosław Nielek and Konrad Grzanek, On explainable recommender systems based on fuzzy rule generation techniques, Springer, Cham, 358-372, 2019, Cites: 5
Ensembles of Rough Set–Based Classifiers
Robert K Nowicki, Ensembles of Rough Set–Based Classifiers, Springer, Cham, 161-184, 2019, Cites: 0
Rough Nearest Neighbour Classifier
Robert K Nowicki, Rough Nearest Neighbour Classifier, Springer, Cham, 133-159, 2019, Cites: 0
Rough Set-Based Classification Systems
Robert K Nowicki, Rough Set-Based Classification Systems, Springer, 2019, Cites: 3

2018 (2)

Random forests for profiling computer network users
Jakub Nowak and Marcin Korytkowski and Robert Nowicki and Rafał Scherer and Agnieszka Siwocha, Random forests for profiling computer network users, Springer, Cham, 734-739, 2018, Cites: 9
Rough neural network ensemble for interval data classification
Robert K Nowicki and Marcin Korytkowski and Rafal Scherer, Rough neural network ensemble for interval data classification, IEEE, 1-7, 2018, Cites: 3

2017 (3)

A new method for classification of imprecise data using fuzzy rough fuzzification
Robert K Nowicki and Janusz T Starczewski, A new method for classification of imprecise data using fuzzy rough fuzzification, Elsevier, 33-52, 2017, Cites: 18
Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible s-boxes
Tomasz Kapuściński and Robert K Nowicki and Christian Napoli, Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible s-boxes, Springer, Cham, 466-476, 2017, Cites: 8
Performance Evaluation of DBN Learning on Intel Multi-and Manycore Architectures
Tomasz Olas and Wojciech K Mleczko and Marcin Wozniak and Robert K Nowicki and Pawel Gepner, Performance Evaluation of DBN Learning on Intel Multi-and Manycore Architectures, Springer, Cham, 565-575, 2017, Cites: 0

2016 (9)

Preprocessing Large Data Sets by the Use of Quick Sort Algorithm
Marcin Wo'zniak and Zbigniew Marszalek and Marcin Gabryel and Robert K Nowicki, Preprocessing Large Data Sets by the Use of Quick Sort Algorithm, 111-121, 2016, Cites: 0
Novel rough neural network for classification with missing data
Robert K Nowicki and Rafal Scherer and Leszek Rutkowski, Novel rough neural network for classification with missing data, IEEE, 820-825, 2016, Cites: 7
Preprocessing large data sets by the use of quick sort algorithm
Marcin Woźniak and Zbigniew Marszałek and Marcin Gabryel and Robert K Nowicki, Preprocessing large data sets by the use of quick sort algorithm, Springer, Cham, 111-121, 2016, Cites: 21
An application of firefly algorithm to position traffic in NoSQL database systems
Marcin Woźniak and Marcin Gabryel and Robert K Nowicki and Bartosz A Nowak, An application of firefly algorithm to position traffic in NoSQL database systems, Springer, Cham, 259-272, 2016, Cites: 15
Application of genetic algorithms in the construction of invertible substitution boxes
Tomasz Kapuściński and Robert K Nowicki and Christian Napoli, Application of genetic algorithms in the construction of invertible substitution boxes, Springer, Cham, 380-391, 2016, Cites: 7
Rough restricted boltzmann machine–new architecture for incomplete input data
Wojciech K Mleczko and Robert K Nowicki and Rafał Angryk, Rough restricted boltzmann machine–new architecture for incomplete input data, Springer, Cham, 114-125, 2016, Cites: 5
Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples
Robert K Nowicki and Bartosz A Nowak and Marcin Woźniak, Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples, Springer, Cham, 243-257, 2016, Cites: 12
Content-based image retrieval optimization by differential evolution
Rafał Grycuk and Marcin Gabryel and Robert Nowicki and Rafał Scherer, Content-based image retrieval optimization by differential evolution, IEEE, 86-93, 2016, Cites: 18
Transient Solution for Queueing Delay Distribution in the GI/M/1/K-type Mode with “Queued” Waking up and Balking
Wojciech M Kempa and Marcin Woźniak and Robert K Nowicki and Marcin Gabryel and Robertas Damaševicius, Transient Solution for Queueing Delay Distribution in the GI/M/1/K-type Mode with “Queued” Waking up and Balking, Springer, Cham, 340-351, 2016, Cites: 9

2015 (9)

Adaptation of RBM learning for intel MIC architecture
Tomasz Olas and Wojciech K Mleczko and Robert K Nowicki and Roman Wyrzykowski and Adam Krzyzak, Adaptation of RBM learning for intel MIC architecture, Springer, Cham, 90-101, 2015, Cites: 5
Adaptation of deep belief networks to modern multicore architectures
Tomasz Olas and Wojciech K Mleczko and Robert K Nowicki and Roman Wyrzykowski, Adaptation of deep belief networks to modern multicore architectures, Springer, Cham, 459-472, 2015, Cites: 5
Design methodology for rough neuro-fuzzy classification with missing data
Robert K Nowicki and Marcin Korytkowski and Bartosz A Nowak and Rafal Scherer, Design methodology for rough neuro-fuzzy classification with missing data, IEEE, 1650-1657, 2015, Cites: 4
Toward work groups classification based on probabilistic neural network approach
Christian Napoli and Giuseppe Pappalardo and Emiliano Tramontana and Robert K Nowicki and Janusz T Starczewski and Marcin Woźniak, Toward work groups classification based on probabilistic neural network approach, Springer, Cham, 79-89, 2015, Cites: 28
Rough deep belief network-application to incomplete handwritten digits pattern classification
Wojciech K Mleczko and Tomasz Kapuściński and Robert K Nowicki, Rough deep belief network-application to incomplete handwritten digits pattern classification, Springer, Cham, 400-411, 2015, Cites: 18
Can we process 2d images using artificial bee colony?
Marcin Woźniak and Dawid Połap and Marcin Gabryel and Robert K Nowicki and Christian Napoli and Emiliano Tramontana, Can we process 2d images using artificial bee colony?, Springer, Cham, 660-671, 2015, Cites: 31
A multiscale image compressor with rbfnn and discrete wavelet decomposition
Marcin Wozniak and Christian Napoli and Emiliano Tramontana and Giacomo Capizzi and Grazia Lo Sciuto and Robert K Nowicki and Janusz T Starczewski, A multiscale image compressor with rbfnn and discrete wavelet decomposition, IEEE, 1-7, 2015, Cites: 27
Novel approach toward medical signals classifier
Marcin Wózniak and Dawid Połap and Robert K Nowicki and Christian Napoli and Giuseppe Pappalardo and Emiliano Tramontana, Novel approach toward medical signals classifier, IEEE, 1-7, 2015, Cites: 25
Multi-class nearest neighbour classifier for incomplete data handling
Bartosz A Nowak and Robert K Nowicki and Marcin Woźniak and Christian Napoli, Multi-class nearest neighbour classifier for incomplete data handling, Springer, Cham, 469-480, 2015, Cites: 36

2014 (7)

On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue
Marcin Woźniak and Wojciech M Kempa and Marcin Gabryel and Robert K Nowicki and Zhifei Shao, On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue, Springer, Cham, 480-491, 2014, Cites: 38
Rough k nearest neighbours for classification in the case of missing input data
Robert Nowicki and Bartosz A Nowak and Marcin Woźniak, Rough k nearest neighbours for classification in the case of missing input data, 196–207, 2014, Cites: 9
Genetic fuzzy classifier with fuzzy rough sets for imprecise data
Janusz T Starczewski and Robert K Nowicki and Bartosz A Nowak, Genetic fuzzy classifier with fuzzy rough sets for imprecise data, IEEE, 1382-1389, 2014, Cites: 9
The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features
Robert K Nowicki and Bartosz A Nowak and Janusz T Starczewski and Krzysztof Cpałka, The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features, IEEE, 3759-3766, 2014, Cites: 10
A novel approach to position traffic in nosql database systems by the use of firefly algorithm
Marcin Woźniak and Marcin Gabryel and Robert Konrad Nowicki and Bartosz Antoni Nowak, A novel approach to position traffic in nosql database systems by the use of firefly algorithm, 2014, Cites: 4
The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets
Bartosz A Nowak and Robert K Nowicki and Janusz T Starczewski and Antonino Marvuglia, The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets, Springer, Cham, 256-266, 2014, Cites: 10
A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning
Marcin Woźniak and Wojciech M Kempa and Marcin Gabryel and Robert K Nowicki, A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning, 2014, Cites: 48

2013 (6)

Modified merge sort algorithm for large scale data sets
Marcin Woźniak and Zbigniew Marszałek and Marcin Gabryel and Robert K Nowicki, Modified merge sort algorithm for large scale data sets, Springer, Berlin, Heidelberg, 612-622, 2013, Cites: 35
On quick sort algorithm performance for large data sets
M Woźniak and Z Marszałek and M Gabryel and RK Nowicki, On quick sort algorithm performance for large data sets, 7-9, 2013, Cites: 10
Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy
Marcin Gabryel and Robert K Nowicki and Marcin Woźniak and Wojciech M Kempa, Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy, Springer, Berlin, Heidelberg, 12-23, 2013, Cites: 33
Triple heap sort algorithm for large data sets
M Woźniak and Z Marszałek and M Gabryel and RK Nowicki, Triple heap sort algorithm for large data sets, 657-665, 2013, Cites: 13
On design of flexible neuro-fuzzy systems for nonlinear modelling
Krzysztof Cpałka and Olga Rebrova and Robert Nowicki and Leszek Rutkowski, On design of flexible neuro-fuzzy systems for nonlinear modelling, Routledge, 706-720, 2013, Cites: 69
A new method of improving classification accuracy of decision tree in case of incomplete samples
Bartosz A Nowak and Robert K Nowicki and Wojciech K Mleczko, A new method of improving classification accuracy of decision tree in case of incomplete samples, Springer, Berlin, Heidelberg, 448-458, 2013, Cites: 9

2012 (4)

Neuro-fuzzy SystemsNeuro-fuzzy systems (NFS)
L Rutkowski and K Cpałka and R Nowicki and A Pokropińska and R Scherer, Neuro-fuzzy SystemsNeuro-fuzzy systems (NFS), Springer, 2069-2081, 2012, Cites: 4
Creating learning sets for control systems using an evolutionary method
Marcin Gabryel and Marcin Woźniak and Robert K Nowicki, Creating learning sets for control systems using an evolutionary method, Springer, Berlin, Heidelberg, 206-213, 2012, Cites: 31
Simulation of the characteristics of the ball movement on a beam by the use of genetic algorithm
Marcin Woźniak and Marcin Gabryel and R Nowicki, Simulation of the characteristics of the ball movement on a beam by the use of genetic algorithm, 19--33, 2012, Cites: 0
Model of decision support system for ball positioning relative to the center of mobile beam
Marcin Woźniak and Marcin Gabryel and R Nowicki, Model of decision support system for ball positioning relative to the center of mobile beam, 2012, Cites: 1

2011 (3)

Learning in rough-neuro-fuzzy system for data with missing values
Bartosz A Nowak and Robert K Nowicki, Learning in rough-neuro-fuzzy system for data with missing values, Springer, Berlin, Heidelberg, 501-510, 2011, Cites: 9
On designing of flexible neuro-fuzzy systems for nonlinear modelling
Krzysztof Cpałka and Olga Rebrova and Robert Nowicki and Leszek Rutkowski, On designing of flexible neuro-fuzzy systems for nonlinear modelling, Springer, Berlin, Heidelberg, 147-154, 2011, Cites: 2
AdaBoost ensemble of DCOG rough–neuro–fuzzy systems
Marcin Korytkowski and Robert Nowicki and Leszek Rutkowski and Rafał Scherer, AdaBoost ensemble of DCOG rough–neuro–fuzzy systems, Springer, Berlin, Heidelberg, 62-71, 2011, Cites: 25

2010 (3)

On non-singleton fuzzification with DCOG defuzzification
Robert K Nowicki and Janusz T Starczewski, On non-singleton fuzzification with DCOG defuzzification, Springer, Berlin, Heidelberg, 168-174, 2010, Cites: 9
MICOG defuzzification rough-neuro-fuzzy system ensemble
Marcin Korytkowski and Robert K Nowicki and Rafał Scherer and Leszek Rutkowski, MICOG defuzzification rough-neuro-fuzzy system ensemble, IEEE, 1-6, 2010, Cites: 3
On classification with missing data using rough-neuro-fuzzy systems
Robert Nowicki, On classification with missing data using rough-neuro-fuzzy systems, De Gruyter Poland, 55, 2010, Cites: 36

2009 (5)

Nonlinear modelling and classification based on the MICOG defuzzification
Robert Nowicki, Nonlinear modelling and classification based on the MICOG defuzzification, Pergamon, e1033-e1047, 2009, Cites: 19
Rough neuro-fuzzy structures for classification with missing data
Robert Nowicki, Rough neuro-fuzzy structures for classification with missing data, IEEE, 1334-1347, 2009, Cites: 63
Rozmyte systemy decyzyjne w zadaniach z ograniczoną wiedzą
Robert K Nowicki, Rozmyte systemy decyzyjne w zadaniach z ograniczoną wiedzą, Akademicka Oficyna Wydawnicza Exit, 2009, Cites: 20
Neuro-fuzzy Systems.
Leszek Rutkowski and Krzysztof Cpalka and Robert Nowicki and Agata Pokropinska and Rafal Scherer, Neuro-fuzzy Systems., 6086-6099, 2009, Cites: 0
Neuro-fuzzy rough classifier ensemble
Marcin Korytkowski and Robert Nowicki and Rafał Scherer, Neuro-fuzzy rough classifier ensemble, Springer, Berlin, Heidelberg, 817-823, 2009, Cites: 27

2008 (4)

Metody projektowania rozmytych sterowników
L Rutkowski and R Nowicki and A Pokropińska, Metody projektowania rozmytych sterowników, 2008, Cites: 0
Information Theory Inspired Weighted Immune Classification Algorithm
Maciej Morkowski and Robert Nowicki, Information Theory Inspired Weighted Immune Classification Algorithm, Springer, Berlin, Heidelberg, 652-660, 2008, Cites: 2
Ensemble of rough-neuro-fuzzy systems for classification with missing features
Marcin Korytkowski and Robert Nowicki and Rafal Scherer and Leszek Rutkowski, Ensemble of rough-neuro-fuzzy systems for classification with missing features, IEEE, 1745-1750, 2008, Cites: 12
On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data
Robert Nowicki, On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data, IEEE, 1239-1253, 2008, Cites: 41

2007 (4)

Modular type-2 neuro-fuzzy systems
Janusz Starczewski and Rafał Scherer and Marcin Korytkowski and Robert Nowicki, Modular type-2 neuro-fuzzy systems, Springer, Berlin, Heidelberg, 570-578, 2007, Cites: 19
Modular rough neuro-fuzzy systems for classification
Rafał Scherer and Marcin Korytkowski and Robert Nowicki and Leszek Rutkowski, Modular rough neuro-fuzzy systems for classification, Springer, Berlin, Heidelberg, 540-548, 2007, Cites: 3
Rough-neuro-fuzzy systems for classification
Krzysztof Cpalka and Robert Nowicki and Leszek Rutkowski, Rough-neuro-fuzzy systems for classification, IEEE, 1-8, 2007, Cites: 2
The role of fungi Malassezia spp. in etiopatology of skin diseases
M Wozniak and R Nowicki, The role of fungi Malassezia spp. in etiopatology of skin diseases, 265, 2007, Cites: 0

2006 (5)

Biologicals used in psoriasis treatment
M Wozniak and R Nowicki, Biologicals used in psoriasis treatment, AD FONTES, 29, 2006, Cites: 0
Rough-neuro-fuzzy system with MICOG defuzzification
Robert Nowicki, Rough-neuro-fuzzy system with MICOG defuzzification, IEEE, 1958-1965, 2006, Cites: 23
Combining logical-type neuro-fuzzy systems
Marcin Korytkowski and Robert Nowicki and Leszek Rutkowski and Rafał Scherer, Combining logical-type neuro-fuzzy systems, Springer, Berlin, Heidelberg, 240-249, 2006, Cites: 1
Isolines of statistical information criteria for relational neuro-fuzzy system design
Agata Pokropińska and Robert Nowicki and Rafał Scherer, Isolines of statistical information criteria for relational neuro-fuzzy system design, Springer, Berlin, Heidelberg, 288-296, 2006, Cites: 1
Merging ensemble of neuro-fuzzy systems
Marcin Korytkowski and Robert Nowicki and Leszek Rutkowski and Rafal Scherer, Merging ensemble of neuro-fuzzy systems, IEEE, 1954-1957, 2006, Cites: 6

2005 (1)

Neuro-fuzzy structures and their comparative analyzes
Robert Nowicki and Agata Pokropińska, Neuro-fuzzy structures and their comparative analyzes, 203-208, 2005, Cites: 4

2004 (4)

Genetic algorithm for database indexing
Marcin Korytkowski and Marcin Gabryel and Robert Nowicki and Rafał Scherer, Genetic algorithm for database indexing, Springer, Berlin, Heidelberg, 1142-1147, 2004, Cites: 2
Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications
Robert Nowicki, Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications, Springer, Berlin, Heidelberg, 510-517, 2004, Cites: 21
Information criterions applied to neuro-fuzzy architectures design
Robert Nowicki and Agata Pokropińska, Information criterions applied to neuro-fuzzy architectures design, Springer, Berlin, Heidelberg, 332-337, 2004, Cites: 20
Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications
Robert Nowicki, Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications, Springer, Berlin, Heidelberg, 518-525, 2004, Cites: 25

2003 (4)

Neuro-fuzzy versus non-parametric approach to system modeling and classification
Robert Nowicki, Neuro-fuzzy versus non-parametric approach to system modeling and classification, Springer, Berlin, Heidelberg, 632-640, 2003, Cites: 2
Soft techniques for bayesian classification
Robert Nowicki and Leszek Rutkowski, Soft techniques for bayesian classification, Physica, Heidelberg, 537-544, 2003, Cites: 15
A hierarchical neuro-fuzzy system based on S-implications
R Nowicki and R Scherer and L Rutkowski, A hierarchical neuro-fuzzy system based on S-implications, IEEE, 321-325, 2003, Cites: 7
On designing of neuro-fuzzy systems
Robert Nowicki and Agata Pokropińska and Yoichi Hayashi, On designing of neuro-fuzzy systems, Springer, Berlin, Heidelberg, 641-649, 2003, Cites: 2

2002 (3)

Rough-Neuro-Fuzzy System for Classification.
Robert Nowicki and Leszek Rutkowski, Rough-Neuro-Fuzzy System for Classification., 463-466, 2002, Cites: 11
A method for learning of hierarchical fuzzy systems
R Nowicki and R Scherer and L Rutkowski, A method for learning of hierarchical fuzzy systems, IOS Press, Amsterdam, 124-129, 2002, Cites: 23
A neuro-fuzzy system based on the hierarchical prioritized structure
R Nowicki and R Scherer and L Rutkowski, A neuro-fuzzy system based on the hierarchical prioritized structure, 192-198, 2002, Cites: 5

2001 (3)

Competitive learning of neuro-fuzzy systems
R Nowicki and D Rutkowska, Competitive learning of neuro-fuzzy systems, 17-19, 2001, Cites: 6
Parallel processing by implication-based neuro-fuzzy systems
Danuta Rutkowska and Robert Nowicki and Yoichi Hayashi, Parallel processing by implication-based neuro-fuzzy systems, Springer, Berlin, Heidelberg, 599-607, 2001, Cites: 7
Neuro-fuzzy system with inference based on bounded product
Danuta Rutkowska and Leszek Rutkowski and Robert Nowicki, Neuro-fuzzy system with inference based on bounded product, 104-109, 2001, Cites: 6

2000 (4)

Systemy rozmyto-neuronowe realizujące różne sposoby rozmytego wnioskowania
RK Nowicki, Systemy rozmyto-neuronowe realizujące różne sposoby rozmytego wnioskowania, 2000, Cites: 1
New neuro-fuzzy architectures
D Rutkowska and R Nowicki, New neuro-fuzzy architectures, 82-87, 2000, Cites: 15
Neuro-fuzzy architectures with various implication operators
Danuta Rutkowska and Robert Nowicki and Leszek Rutkowski, Neuro-fuzzy architectures with various implication operators, Physica, Heidelberg, 214-219, 2000, Cites: 14
Implication-based neuro-fuzzy architectures
D Rutkowska and R Nowicki, Implication-based neuro-fuzzy architectures, 675-701, 2000, Cites: 51

1999 (6)

Singleton and non-singleton fuzzy systems with nonparametric defuzzification
D Rutkowska and R Nowicki and L Rutkowski, Singleton and non-singleton fuzzy systems with nonparametric defuzzification, Springer-Verlag, 292-301, 1999, Cites: 13
Neuro-fuzzy system with inference process based on Zadeh implication
D Rutkowska and R Nowicki and L Rutkowski, Neuro-fuzzy system with inference process based on Zadeh implication, 597-602, 1999, Cites: 9
Fuzzy inference neural networks based on destructive and constructive approaches and their application to classification
R Nowicki and D Rutkowska, Fuzzy inference neural networks based on destructive and constructive approaches and their application to classification, 294-301, 1999, Cites: 8
On Processing of Noisy Data by Fuzzy Inference Neural Networks.
Danuta Rutkowska and Leszek Rutkowski and Robert Nowicki, On Processing of Noisy Data by Fuzzy Inference Neural Networks., 314-318, 1999, Cites: 8
Constructive and destructive approach to neuro fuzzy systems
D Rutkowska and R Nowicki, Constructive and destructive approach to neuro fuzzy systems, 100-105, 1999, Cites: 8
Department of Computer Engineering Technical University of Czestochowa
Danuta Rutkowska and Robert Nowicki and Leszek Rutkowski, Department of Computer Engineering Technical University of Czestochowa, Physica, 292, 1999, Cites: 0

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