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Paweł Różycki
Paweł Różycki
Unknown affiliation
Verified email at dmt.com.pl
Title
Cited by
Cited by
Year
A novel RBF training algorithm for short-term electric load forecasting and comparative studies
C Cecati, J Kolbusz, P Różycki, P Siano, BM Wilamowski
IEEE Transactions on industrial Electronics 62 (10), 6519-6529, 2015
2582015
Fast and efficient second-order method for training radial basis function networks
T Xie, H Yu, J Hewlett, P Rózycki, B Wilamowski
IEEE transactions on neural networks and learning systems 23 (4), 609-619, 2012
1402012
Nonlinear system modeling using RBF networks for industrial application
X Meng, P Rozycki, JF Qiao, BM Wilamowski
IEEE transactions on industrial informatics 14 (3), 931-940, 2017
892017
Recovery of the control plane after failures in ASON/GMPLS networks
A Jajszczyk, P Rozycki
IEEE network 20 (1), 4-10, 2006
532006
A hybrid constructive algorithm for single-layer feedforward networks learning
X Wu, P Różycki, BM Wilamowski
IEEE Transactions on Neural Networks and Learning Systems 26 (8), 1659-1668, 2014
512014
The study of architecture MLP with linear neurons in order to eliminate the “vanishing gradient” problem
J Kolbusz, P Rozycki, BM Wilamowski
International conference on artificial intelligence and soft computing, 97-106, 2017
352017
Failure detection and notification in GMPLS control plane
P Rozycki, J Korniak, A Jajszczyk
2007 Workshop on GMPLS Performance: Control Plane Resilience, 1-6, 2007
182007
Dedicated deep neural network architectures and methods for their training
P Różycki, J Kolbusz, BM Wilamowski
2015 IEEE 19th International Conference on Intelligent Engineering Systems …, 2015
132015
GMPLS-simulation tools
J Korniak, P Rózycki
Proceedings of the 1st Conference Tools of Information Technology, 20-25, 2006
112006
Polynet: a polynomial-based learning machine for universal approximation
MS Pukish, P Różycki, BM Wilamowski
IEEE Transactions on Industrial Informatics 11 (3), 708-716, 2015
102015
Using Parity-N Problems as a Way to Compare Abilities of Shallow, Very Shallow and Very Deep Architectures
P Różycki, J Kolbusz, T Bartczak, BM Wilamowski
International Conference on Artificial Intelligence and Soft Computing, 112-122, 2015
82015
Error back propagation algorithm with adaptive learning rate
J Kolbusz, P Rozycki, O Lysenko, BM Wilamowski
2019 International Conference on Information and Digital Technologies (IDT …, 2019
72019
Estimation of deep neural networks capabilities using polynomial approach
P Rozycki, J Kolbusz, R Korostenskyi, BM Wilamowski
International Conference on Artificial Intelligence and Soft Computing, 136-147, 2016
62016
Signaling improvements for GMPLS control plane
J Korniak, P Rozycki
Proceedings of the 2nd Conference Tools of the Information Technology, 29-34, 2007
62007
Implementation of deep neural networks for industry applications
P Rozycki, J Kolbusz, G Krzos, BM Wilamowski
IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society …, 2018
52018
Estimation of deep neural networks capabilities based on a trigonometric approach
P Rozycki, J Kolbusz, BM Wilamowski
2016 IEEE 20th Jubilee International Conference on Intelligent Engineering …, 2016
52016
Spectral image recognition using artificial dynamic neural network in information resonance mode
I Peleshchak, R Peleshchak, V Lytvyn, J Kopka, M Wrzesien, J Korniak, ...
Artificial Intelligence and Industrial Applications: Smart Operation …, 2021
32021
Innowacyjna Gmina. Informatyka w jednostkach samorządu terytorialnego
M Hajder
Wyższa Szkoła Informatyki i Zarządzania z siedzibą w Rzeszowie, 2014
32014
The weighted graphs approach for the GMPLS network reliability enhancement
P Rozycki, A Jajszczyk
International Congress on Ultra Modern Telecommunications and Control …, 2010
32010
Service availability analysis of GMPLS network
J Korniak, P Rozycki
2010 14th International Telecommunications Network Strategy and Planning …, 2010
32010
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