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Andrzej Przybył
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Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation
KC Leszek Rutkowski, Andrzej Przybył
IEEE Transactions on Industrial Electronics 59 (2), 1238-1247, 2012
101*2012
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
K Cpałka, K Łapa, A Przybył, M Zalasiński
Neurocomputing 135, 203-217, 2014
862014
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach
L Rutkowski, A Przybył, K Cpałka, MJ Er
International Conference on Artificial Intelligence and Soft Computing, 645-650, 2010
562010
A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Ł Bartczuk, A Przybył, K Cpałka
International Journal of Applied Mathematics and Computer Science 26 (3), 2016
532016
A new approach to designing interpretable models of dynamic systems
K Łapa, A Przybył, K Cpałka
International Conference on Artificial Intelligence and Soft Computing, 523-534, 2013
472013
Some aspects of evolutionary designing optimal controllers
J Szczypta, A Przybył, K Cpałka
International Conference on Artificial Intelligence and Soft Computing, 91-100, 2013
462013
A new approach to design of control systems using genetic programming
K Cpalka, K Łapa, A Przybył
Information technology and control 44 (4), 433-442, 2015
452015
A new method to construct of interpretable models of dynamic systems
A Przybył, K Cpałka
International Conference on Artificial Intelligence and Soft Computing, 697-705, 2012
432012
A new algorithm for identification of significant operating points using swarm intelligence
P Dziwiński, Ł Bartczuk, A Przybył, ED Avedyan
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
332014
New method for nonlinear fuzzy correction modelling of dynamic objects
Ł Bartczuk, A Przybył, P Koprinkova-Hristova
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
272014
Genetic programming algorithm for designing of control systems
K Cpalka, K Łapa, A Przybył
Information Technology and Control 47 (4), 668-683, 2018
212018
Genetic Algorithm for Observer Parameters Tuning in Sensorless Induction Motor Drive.
AP Jerzy Jelonkiewicz
Neural Networks and Soft Computing. Proceedings of the Sixth International …, 2003
21*2003
HARDWARE IMPLEMENTATION OF A TAKAGI-SUGENO NEURO-FUZZY SYSTEM OPTIMIZED BY A POPULATION ALGORITHM
P Dziwinski, A Przybył, P Trippner, J Paszkowski, Y Hayashi
Journal of Artificial Intelligence and Soft Computing Research 11 (3), 243 - 266, 2021
192021
Hybrid state variables-fuzzy logic modelling of nonlinear objects
Ł Bartczuk, A Przybył, P Dziwiński
Artificial Intelligence and Soft Computing: 12th International Conference …, 2013
192013
Distributed control system based on real time ethernet for computer numerical controlled machine tool
A Przybyl, J Smolag, P Kimla
Przeglad Elektrotechniczny 86 (2), 342-346, 2010
172010
The method of hardware implementation of fuzzy systems on FPGA
A Przybył, MJ Er
Artificial Intelligence and Soft Computing: 15th International Conference …, 2016
132016
The idea for the integration of neuro-fuzzy hardware emulators with real-time network
A Przybył, MJ Er
International Conference on Artificial Intelligence and Soft Computing, 279-294, 2014
122014
Evolutionary approach with multiple quality criteria for controller design
J Szczypta, A Przybył, L Wang
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
122014
Fixed-point arithmetic unit with a scaling mechanism for FPGA-based embedded systems
A Przybył
Electronics 10 (10), 1164, 2021
112021
Negative space-based population initialization algorithm (NSPIA)
K Łapa, K Cpałka, A Przybył, K Grzanek
Artificial Intelligence and Soft Computing: 17th International Conference …, 2018
112018
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