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Contact:
Room: 155

Position:
Full Professor

Research teams:
Nowe systemy głębokiego uczenia i ich zastosowania

Classes:
Seminarium dyplomowe i przygotowanie pracy dyplomowej sem
Systemy rozmyte i przetwarzanie niepewności lab
Systemy rozmyte i przetwarzanie niepewności wyk
Prof. PhD DSc Eng Robert Nowicki
Office hours: wtorek 10-12, p. 2 WIMiI

Papers (78)

2021 (1)

Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values
Nowicki R.K., Seliga R., elasko D., Hayashi Y., Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 307-318, 2021, Cites: 5

2020 (1)

Rough Support Vector Machine for Classification with Interval and Incomplete Data
Nowicki R.K., Grzanek K., Hayashi Y., Rough Support Vector Machine for Classification with Interval and Incomplete Data, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 47-56, 2020, Cites: 14

2019 (15)

Final Remarks
Nowicki R.K., Final Remarks, Studies in Computational Intelligence, 802, 802, 185-188, 2019, Cites: 0
Rough Neural Network Classifier
Nowicki R.K., Rough Neural Network Classifier, Studies in Computational Intelligence, 802, 802, 95-132, 2019, Cites: 0
Ensembles of Rough Set–Based Classifiers
Nowicki R.K., Ensembles of Rough Set–Based Classifiers, Studies in Computational Intelligence, 802, 802, 161-184, 2019, Cites: 0
Sequential Data Mining of Network Traffic in URL Logs
Korytkowski M., Nowak J., Nowicki R., Milkowska K., Scherer M., Goetzen P., Sequential Data Mining of Network Traffic in URL Logs, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 125-130, 2019, Cites: 0
Extended Possibilistic Fuzzification for Classification
Nowicki R.K., Starczewski J.T., Grycuk R., Extended Possibilistic Fuzzification for Classification, International Joint Conference on Computational Intelligence, 1, 1, 343-350, 2019, Cites: 0
Rough Fuzzy Classification Systems
Nowicki R.K., Rough Fuzzy Classification Systems, Studies in Computational Intelligence, 802, 802, 17-70, 2019, Cites: 3
Fuzzy–rough Fuzzification in General FL Classifiers
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy–rough Fuzzification in General FL Classifiers, International Joint Conference on Computational Intelligence, 1, 1, 335-342, 2019, Cites: 0
Multilayer architecture for content-based image retrieval systems
Grycuk R., Najgebauer P., Nowicki R., Scherer R., Multilayer architecture for content-based image retrieval systems, Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019, 119-126, 2019, Cites: 1
Introduction
Nowicki R.K., Introduction, Studies in Computational Intelligence, 802, 802, 1-6, 2019, Cites: 0
Extended possibilistic fuzzification for classification
Nowicki R.K., Starczewski J.T., Grycuk R., Extended possibilistic fuzzification for classification, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 343-350, 2019, Cites: 1
On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques
Rutkowski T., Lapa K., Nowicki R., Nielek R., Grzanek K., On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 358-372, 2019, Cites: 7
Rough Nearest Neighbour Classifier
Nowicki R.K., Rough Nearest Neighbour Classifier, Studies in Computational Intelligence, 802, 802, 133-159, 2019, Cites: 2
Fuzzy-rough fuzzification in general FL classifiers
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy-rough fuzzification in general FL classifiers, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 335-342, 2019, Cites: 2
Fuzzy Rough Classification Systems
Nowicki R.K., Fuzzy Rough Classification Systems, Studies in Computational Intelligence, 802, 802, 71-93, 2019, Cites: 0
Rough Set Theory Fundamentals
Nowicki R.K., Rough Set Theory Fundamentals, Studies in Computational Intelligence, 802, 802, 7-16, 2019, Cites: 2

2018 (3)

Rough neural network ensemble for interval data classification
Nowicki R.K., Korytkowski M., Scherer R., Rough neural network ensemble for interval data classification, IEEE International Conference on Fuzzy Systems, 2018-July, 2018-July, 2018, Cites: 3
Random forests for profiling computer network users
Nowak J., Korytkowski M., Nowicki R., Scherer R., Siwocha A., Random forests for profiling computer network users, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 734-739, 2018, Cites: 11
Performance evaluation of DBN learning on intel multi- and manycore architectures
Olas T., Mleczko W.K., Wozniak M., Nowicki R.K., Gepner P., Performance evaluation of DBN learning on intel multi- and manycore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10777 LNCS, 10777 LNCS, 565-575, 2018, Cites: 0

2017 (2)

Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes
Kapuscinski T., Nowicki R.K., Napoli C., Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 466-476, 2017, Cites: 11
A new method for classification of imprecise data using fuzzy rough fuzzification
Nowicki R.K., Starczewski J.T., A new method for classification of imprecise data using fuzzy rough fuzzification, Information Sciences, 414, 414, 33-52, 2017, Cites: 25

2016 (9)

Adaptation of deep belief networks to modern multicore architectures
Olas T., Mleczko W.K., Nowicki R.K., Wyrzykowski R., Adaptation of deep belief networks to modern multicore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9573, 9573, 459-472, 2016, Cites: 5
Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples
Nowicki R.K., Nowak B.A., Wozniak M., Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples, Advances in Intelligent Systems and Computing, 416, 416, 243-257, 2016, Cites: 13
An application of firefly algorithm to position traffic in NoSQL database systems
Wozniak M., Gabryel M., Nowicki R.K., Nowak B.A., An application of firefly algorithm to position traffic in NoSQL database systems, Advances in Intelligent Systems and Computing, 416, 416, 259-272, 2016, Cites: 16
Application of genetic algorithms in the construction of invertible substitution boxes
Kapuscinski T., Nowicki R.K., Napoli C., Application of genetic algorithms in the construction of invertible substitution boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 380-391, 2016, Cites: 14
Preprocessing large data sets by the use of quick sort algorithm
Wozniak M., Marszalek Z., Gabryel M., Nowicki R.K., Preprocessing large data sets by the use of quick sort algorithm, Advances in Intelligent Systems and Computing, 364, 364, 111-121, 2016, Cites: 23
Content-based image retrieval optimization by differential evolution
Grycuk R., Gabryel M., Nowicki R., Scherer R., Content-based image retrieval optimization by differential evolution, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, 86-93, 2016, Cites: 17
Novel rough neural network for classification with missing data
Nowicki R.K., Scherer R., Rutkowski L., Novel rough neural network for classification with missing data, 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, 820-825, 2016, Cites: 5
Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking
Kempa W.M., Wozniak M., Nowicki R.K., Gabryel M., Damasevicius R., Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 340-351, 2016, Cites: 6
Rough restricted Boltzmann machine -New architecture for incomplete input data
Mleczko W.K., Nowicki R.K., Angryk R., Rough restricted Boltzmann machine -New architecture for incomplete input data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 114-125, 2016, Cites: 2

2015 (8)

Rough deep belief network - application to incomplete handwritten digits pattern classification
Mleczko W.K., Kapuscinski T., Nowicki R.K., Rough deep belief network - application to incomplete handwritten digits pattern classification, Communications in Computer and Information Science, 538, 538, 400-411, 2015, Cites: 17
Can we process 2D images using artificial bee colony?
Wozniak M., Polap D., Gabryel M., Nowicki R.K., Napoli C., Tramontana E., Can we process 2D images using artificial bee colony?, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 660-671, 2015, Cites: 36
Novel approach toward medical signals classifier
Wozniak M., Polap D., Nowicki R.K., Napoli C., Pappalardo G., Tramontana E., Novel approach toward medical signals classifier, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 36
A multiscale image compressor with RBFNN and Discrete Wavelet decomposition
Wozniak M., Napoli C., Tramontana E., Capizzi G., Lo Sciuto G., Nowicki R.K., Starczewski J.T., A multiscale image compressor with RBFNN and Discrete Wavelet decomposition, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 36
Design methodology for rough neuro-fuzzy classification with missing data
Nowicki R.K., Korytkowski M., Nowak B.A., Scherer R., Design methodology for rough neuro-fuzzy classification with missing data, Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015, 1650-1657, 2015, Cites: 5
Toward work groups classification based on probabilistic neural network approach
Napoli C., Pappalardo G., Tramontana E., Nowicki R.K., Starczewski J.T., Wozniak M., Toward work groups classification based on probabilistic neural network approach, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 79-89, 2015, Cites: 36
Multi-class nearest neighbour classifier for incomplete data handling
Nowak B.A., Nowicki R.K., Wozniak M., Napoli C., Multi-class nearest neighbour classifier for incomplete data handling, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 469-480, 2015, Cites: 36
Adaptation of RBM learning for intel MIC architecture
Olas T., Mleczko W.K., Nowicki R.K., Wyrzykowski R., Krzyzak A., Adaptation of RBM learning for intel MIC architecture, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 90-101, 2015, Cites: 7

2014 (5)

A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning
Wozniak M., Kempa W.M., Gabryel M., Nowicki R.K., A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning, International Journal of Applied Mathematics and Computer Science, 24, 24, 887-900, 2014, Cites: 45
The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets
Nowak B.A., Nowicki R.K., Starczewski J.T., Marvuglia A., The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 256-266, 2014, Cites: 10
Genetic fuzzy classifier with fuzzy rough sets for imprecise data
Starczewski J.T., Nowicki R.K., Nowak B.A., Genetic fuzzy classifier with fuzzy rough sets for imprecise data, IEEE International Conference on Fuzzy Systems, 1382-1389, 2014, Cites: 8
On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue
Wozniak M., Kempa W.M., Gabryel M., Nowicki R.K., Shao Z., On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 480-491, 2014, Cites: 32
The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features
Nowicki R.K., Nowak B.A., Starczewski J.T., Cpalka K., The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features, Proceedings of the International Joint Conference on Neural Networks, 3759-3766, 2014, Cites: 10

2013 (4)

A new method of improving classification accuracy of decision tree in case of incomplete samples
Nowak B.A., Nowicki R.K., Mleczko W.K., A new method of improving classification accuracy of decision tree in case of incomplete samples, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 448-458, 2013, Cites: 8
Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy
Gabryel M., Nowicki R.K., Wozniak M., Kempa W.M., Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 12-23, 2013, Cites: 29
Modified merge sort algorithm for large scale data sets
Wozniak M., Marszalek Z., Gabryel M., Nowicki R.K., Modified merge sort algorithm for large scale data sets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 612-622, 2013, Cites: 28
On design of flexible neuro-fuzzy systems for nonlinear modelling
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On design of flexible neuro-fuzzy systems for nonlinear modelling, International Journal of General Systems, 42, 42, 706-720, 2013, Cites: 66

2012 (3)

Creating learning sets for control systems using an evolutionary method
Gabryel M., Wozniak M., K. Nowicki R., Creating learning sets for control systems using an evolutionary method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7269 LNCS, 7269 LNCS, 206-213, 2012, Cites: 26
Learning in rough-neuro-fuzzy system for data with missing values
Nowak B.A., Nowicki R.K., Learning in rough-neuro-fuzzy system for data with missing values, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7203 LNCS, 7203 LNCS, 501-510, 2012, Cites: 3
Neuro-fuzzy systems
Rutkowski L., Cpalka K., Nowicki R., Pokropinska A., Scherer R., Neuro-fuzzy systems, Computational Complexity: Theory, Techniques, and Applications, 9781461418009, 9781461418009, 2069-2081, 2012, Cites: 4

2011 (2)

On designing of flexible neuro-fuzzy systems for nonlinear modelling
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On designing of flexible neuro-fuzzy systems for nonlinear modelling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6743 LNAI, 6743 LNAI, 147-154, 2011, Cites: 2
AdaBoost ensemble of DCOG rough-neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., AdaBoost ensemble of DCOG rough-neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6922 LNAI, 6922 LNAI, 62-71, 2011, Cites: 25

2010 (3)

On non-singleton fuzzification with DCOG defuzzification
Nowicki R.K., Starczewski J.T., On non-singleton fuzzification with DCOG defuzzification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 168-174, 2010, Cites: 7
MICOG defuzzification rough-neuro-fuzzy system ensemble
Korytkowski M., Nowicki R.K., Scherer R., Rutkowski L., MICOG defuzzification rough-neuro-fuzzy system ensemble, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010, Cites: 5
On classification with missing data using rough-neuro-fuzzy systems
Nowicki R.K., On classification with missing data using rough-neuro-fuzzy systems, International Journal of Applied Mathematics and Computer Science, 20, 20, 55-67, 2010, Cites: 36

2009 (3)

Nonlinear modelling and classification based on the MICOG defuzzification
Nowicki R., Nonlinear modelling and classification based on the MICOG defuzzification, Nonlinear Analysis, Theory, Methods and Applications, 71, 71, 2009, Cites: 16
Rough neuro-fuzzy structures for classification with missing data
Nowicki R., Rough neuro-fuzzy structures for classification with missing data, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39, 39, 1334-1347, 2009, Cites: 61
Neuro-fuzzy rough classifier ensemble
Korytkowski M., Nowicki R., Scherer R., Neuro-fuzzy rough classifier ensemble, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5768 LNCS, 5768 LNCS, 817-823, 2009, Cites: 27

2008 (5)

Ensemble of rough-neuro-fuzzy systems for classification with missing features
Korytkowski M., Nowicki R., Scherer R., Rutkowski L., Ensemble of rough-neuro-fuzzy systems for classification with missing features, IEEE International Conference on Fuzzy Systems, 1745-1750, 2008, Cites: 14
Information theory inspired weighted immune classification algorithm
Morkowski M., Nowicki R., Information theory inspired weighted immune classification algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 652-660, 2008, Cites: 0
Modular rough neuro-fuzzy systems for classification
Scherer R., Korytkowski M., Nowicki R., Rutkowski L., Modular rough neuro-fuzzy systems for classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 540-548, 2008, Cites: 3
On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data
Nowicki R., On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data, IEEE Transactions on Knowledge and Data Engineering, 20, 20, 1239-1253, 2008, Cites: 44
Modular type-2 neuro-fuzzy systems
Starczewski J., Scherer R., Korytkowski M., Nowicki R., Modular type-2 neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 570-578, 2008, Cites: 20

2007 (1)

Rough-neuro-fuzzy systems for classification
Cpalka K., Nowicki R., Rutkowski L., Rough-neuro-fuzzy systems for classification, Proceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007, 1-8, 2007, Cites: 3

2006 (4)

Merging ensemble of neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Merging ensemble of neuro-fuzzy systems, IEEE International Conference on Fuzzy Systems, 1954-1957, 2006, Cites: 7
Isolines of statistical information criteria for relational neuro-fuzzy system design
Pokropinska A., Nowicki R., Scherer R., Isolines of statistical information criteria for relational neuro-fuzzy system design, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 288-296, 2006, Cites: 1
Combining logical-type neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Combining logical-type neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 240-249, 2006, Cites: 1
Rough-neuro-fuzzy system with MICOG defuzzification
Nowicki R., Rough-neuro-fuzzy system with MICOG defuzzification, IEEE International Conference on Fuzzy Systems, 1958-1965, 2006, Cites: 24

2004 (6)

Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications
Nowicki R., Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 518-525, 2004, Cites: 22
Genetic algorithm for database indexing
Korytkowski M., Gabryel M., Nowicki R., Scherer R., Genetic algorithm for database indexing, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 1142-1147, 2004, Cites: 2
Information criterions applied to neuro-fuzzy architectures design
Nowicki R., Pokropinska A., Information criterions applied to neuro-fuzzy architectures design, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 332-337, 2004, Cites: 19
On designing of neuro-fuzzy systems
Nowicki R., Pokropinska A., Hayashi Y., On designing of neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 641-649, 2004, Cites: 1
Neuro-fuzzy versus non-parametric approach to system modeling and classification
Nowicki R., Neuro-fuzzy versus non-parametric approach to system modeling and classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 632-640, 2004, Cites: 0
Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications
Nowicki R., Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 510-517, 2004, Cites: 19

2003 (1)

A Hierarchical Neuro-Fuzzy System Based on S-Implications
Nowicki R., Scherer R., Rutkowski L., A Hierarchical Neuro-Fuzzy System Based on S-Implications, Proceedings of the International Joint Conference on Neural Networks, 1, 1, 321-325, 2003, Cites: 5

2002 (1)

Parallel processing by implication-based neuro-fuzzy systems
Rutkowska D., Nowicki R., Hayashi Y., Parallel processing by implication-based neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2328, 2328, 599-607, 2002, Cites: 4

2001 (1)

Neuro-fuzzy systems with inference based on bounded product
Rutkowska D., Rutkowski L., Nowicki R., Neuro-fuzzy systems with inference based on bounded product, Advances in Neural Networks and Applications, 104-109, 2001, Cites: 5

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