Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties
© 2020 by the authors. In practical applications, stochastic effects are normally viewed as the major sources that lead to the system's unwilling behaviours when modelling real neural systems. As such, the research on network models with stochastic effects is significant. In view of this, in th...
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th-cmuir.6653943832-707152020-10-14T08:39:51Z Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties Pharunyou Chanthorn Grienggrai Rajchakit Jenjira Thipcha Chanikan Emharuethai Ramalingam Sriraman Chee Peng Lim Raja Ramachandran Mathematics © 2020 by the authors. In practical applications, stochastic effects are normally viewed as the major sources that lead to the system's unwilling behaviours when modelling real neural systems. As such, the research on network models with stochastic effects is significant. In view of this, in this paper, we analyse the issue of robust stability for a class of uncertain complex-valued stochastic neural networks (UCVSNNs) with time-varying delays. Based on the real-imaginary separate-type activation function, the original UCVSNN model is analysed using an equivalent representation consisting of two real-valued neural networks. By constructing the proper Lyapunov-Krasovskii functional and applying Jensen's inequality, a number of sufficient conditions can be derived by utilizing Ito's formula, the homeomorphism principle, the linear matrix inequality, and other analytic techniques. As a result, new sufficient conditions to ensure robust, globally asymptotic stability in the mean square for the considered UCVSNN models are derived. Numerical simulations are presented to illustrate the merit of the obtained results. 2020-10-14T08:39:51Z 2020-10-14T08:39:51Z 2020-05-01 Journal 22277390 2-s2.0-85085523418 10.3390/MATH8050742 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85085523418&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70715 |
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Mathematics Pharunyou Chanthorn Grienggrai Rajchakit Jenjira Thipcha Chanikan Emharuethai Ramalingam Sriraman Chee Peng Lim Raja Ramachandran Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
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© 2020 by the authors. In practical applications, stochastic effects are normally viewed as the major sources that lead to the system's unwilling behaviours when modelling real neural systems. As such, the research on network models with stochastic effects is significant. In view of this, in this paper, we analyse the issue of robust stability for a class of uncertain complex-valued stochastic neural networks (UCVSNNs) with time-varying delays. Based on the real-imaginary separate-type activation function, the original UCVSNN model is analysed using an equivalent representation consisting of two real-valued neural networks. By constructing the proper Lyapunov-Krasovskii functional and applying Jensen's inequality, a number of sufficient conditions can be derived by utilizing Ito's formula, the homeomorphism principle, the linear matrix inequality, and other analytic techniques. As a result, new sufficient conditions to ensure robust, globally asymptotic stability in the mean square for the considered UCVSNN models are derived. Numerical simulations are presented to illustrate the merit of the obtained results. |
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Journal |
author |
Pharunyou Chanthorn Grienggrai Rajchakit Jenjira Thipcha Chanikan Emharuethai Ramalingam Sriraman Chee Peng Lim Raja Ramachandran |
author_facet |
Pharunyou Chanthorn Grienggrai Rajchakit Jenjira Thipcha Chanikan Emharuethai Ramalingam Sriraman Chee Peng Lim Raja Ramachandran |
author_sort |
Pharunyou Chanthorn |
title |
Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
title_short |
Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
title_full |
Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
title_fullStr |
Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
title_full_unstemmed |
Robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
title_sort |
robust stability of complex-valued stochastic neural networks with time-varying delays and parameter uncertainties |
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2020 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85085523418&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70715 |
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