Further Robust Dissipativity Analysis of Uncertain Stochastic Generalized Neural Networks With Markovian Jump Parameters

Pharunyou Chanthorn; Grienggrai Rajchakit; Jenjira Thipcha; Chanikan Emharuethai; Ramalingam Sriraman

doi:10.20944/preprints202004.0048.v1

How to cite: Chanthorn, P.; Rajchakit, G.; Thipcha, J.; Emharuethai, C.; Sriraman, R. Further Robust Dissipativity Analysis of Uncertain Stochastic Generalized Neural Networks With Markovian Jump Parameters. Preprints 2020, 2020040048. https://doi.org/10.20944/preprints202004.0048.v1 Chanthorn, P.; Rajchakit, G.; Thipcha, J.; Emharuethai, C.; Sriraman, R. Further Robust Dissipativity Analysis of Uncertain Stochastic Generalized Neural Networks With Markovian Jump Parameters. Preprints 2020, 2020040048. https://doi.org/10.20944/preprints202004.0048.v1

Abstract

This paper analyzes the robust dissipativity of uncertain stochastic generalized neural networks (USGNNs) with Markovian jumping parameters and time-varying delays. In practical applications most of the systems refer to uncertainties, hence, the norm-bounded parameter uncertainties and stochastic disturbance are considered. Then, by constructing an appropriate Lyapunov-Krasovskii functional (LKF) and by employing integral inequalities LMI-based sufficient conditions of the considered systems are established. Numerical simulations are given to show the merit of the presented results.

Keywords

Subject

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Further Robust Dissipativity Analysis of Uncertain Stochastic Generalized Neural Networks With Markovian Jump Parameters

Abstract

Keywords

Subject

Comments (0)