Pavlo Tymoshchuk

Previous Scheduled Teaching

Published Intellectual Contributions

Abstracts and Proceedings

• Tymoshchuk, P. (2024). A MATHEMATICAL MODEL OF TRACKING CONROL NEURAL NETWORK FOR THE KNOWN AFFINE IN THE INPUTS DISCRETE-TIME NONLINEAR SYSTEMS. Analysis, Power Supply and Control of Electrical Systems. Gliwice-Ustron, Silesian University of Technology. https://www.polsl.pl/re3/speto/
• Tymoshchuk, P. (2023). A model of tracking control neural network for the known affine continuous-time nonlinear system. Analysis, Power Supply and Control of Electrical Systems. Gliwice-Ustron, SILESIAN UNIVERSITY OF TECHNOLOGY, WARSAW UNIVERSITY OF TECHNOLOGY, POLISH SOCIETY OF THEORETICAL AND APPLIED ELECTRICAL ENGINEERING, COMMITTEE ON ELECTRICAL ENGINEERING OF THE POLISH ACADEMY OF SCIENCES, POLISH SECTION OF IEEE. https://www.polsl.pl/re3/en/home-2/speto/

Book

• Tymoshchuk, P.V., Lobur, M.V. (2020). Principles of Artificial Neural Networks and Their Applications: Tutorial. N/A.
• Tymoshchuk, P. (2010). Artificial Neural Networks: Tutorial (in Ukrainian).
• Tymoshchuk, P., Lobur, M. Basic Theory of Neural Network Design: Tutorial (in Ukrainian).

Book Chapter

• Tymoshchuk, P. (2023). A NEURAL NETWORK TRACKING CONTROL FOR THE KNOWN AFFINE CONTINUOUS-TIME NONLINEAR SYSTEM. Gliwice, Silesian University of Technology.

Conference Proceeding

• Tymoshchuk, P., Pastyrska. (2021). A Model Analysis for Embedded Control of Known Continuous-Time Scalar Nonlinear Systems. Proc. of the XVII-th International Conf. on “Perspective Technologies and Methods in MEMS Design”.
• Tymoshchuk, P. (2021). Design of parallel rank-order filtering system based on neural circuits of discrete-time. Proc. XVIth Int. Conf. “The Experience of Designing and Application of CAD Systems”.
• Tymoshchuk, P. (2021). Design of Parallel Sorting System Using Discrete-Time Neural Circuit Model.
• Tymoshchuk, P. (2020). Optimal control for continuous-time scalar nonlinear systems with known dynamics. Other.
• Tymoshchuk, P. A neural circuit model of adaptive robust tracking control for continuous-time nonlinear systems.
• Tymoshchuk, P. (2013). A fast analogue K-winners-take-all neural circuit. Other.
• Tymoshchuk, P. Continuous-time model of analogue K-winners-take-all neural circuit. Other.
• Tymoshchuk, P., Kaszkurewicz, E. A Winner-take-all circuit based on second order Hopfield neural networks as building blocks. Other.

Journal Article

• Tymoshchuk, P. (2024). Neural network optimal control for discrete-time nonlinear systems with known internal dynamics. Neural Computing and Applications. Springer.
• Tymoshchuk, P.V., Wunsch, D.C. (2019). Design of a K-winners-take-all model with a binary spike train. IEEE Transactions. N/A. 49 (8) 3131-3140. New York, NY, USA, IEEE.
• Tymoshchuk, P. (2013). A model of analogue K-winners-take-all neural circuit. Neural Networks. 42 (N/A) 44-61. United Kingdom, Elsevier.
• Tymoshchuk, P. (2009). A discrete-time dynamic K-winners-take-all neural circuit. Neurocomputing. 22 (N/A) 3191-3202. United Kingdom, Elsevier.
• Tymoshchuk, P., Kaszkurewicz, E. (2004). A winner-take-all circuit using neural networks as building blocks. Neurocomputing. 64 (N/A) 375-396. United Kingdom, Elsevier.

Contracts, Grants and Sponsored Research

Fellowship

• Tymoshchuk, P., "A Tracking Control Neural Network for Known Affine Discrete-Time Nonlinear Systems," sponsored by CAHSI Local Research Experiences for Undergraduates Program, Local, $5000 Funded. (2024 - 2024).
• Tymoshchuk, P.V., "Faculty First Flight," sponsored by University of North Texas, University of North Texas, $500 Funded. (2022 - 2023).
• Tymoshchuk, P. (Principal), "Optimal Control Discrete-Time Neural Network for Nonlinear Systems with Known Dynamics," sponsored by CAHSI Local Research Experiences for Undergraduates Program, Local, $4000 Funded. (2023 - 2023).

Grant - Research

• Tymoshchuk, P. (Principal), "Spiking K-Winners-Take-All Neural Circuit and its Application for Parallel Rank-Order Filtering and Parallel Sorting," sponsored by Fulbright Scholar Program, International, $28000 Funded. (2015 - 2016).
• Tymoshchuk, P. (Principal), "A Winner-Take-All Circuit Using Second Order Hopfield Neural Networks as Building Blocks," sponsored by National Council of Scientific and Technological Development of Brazil, National, $15000 Funded. (2001 - 2002).