Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Stochastic disturbances often cause undesirable characteristics in real-world system modeling. As a result, investigations on stochastic disturbances in neural network (NN) modeling are important. In this study, stochastic disturbances are co...

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Main Authors: Ramalingam Sriraman, Grienggrai Rajchakit, Chee Peng Lim, Pharunyou Chanthorn, Rajendran Samidurai
Format: Journal
Published: 2020
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/70392
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spelling th-cmuir.6653943832-703922020-10-14T08:39:49Z Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis Ramalingam Sriraman Grienggrai Rajchakit Chee Peng Lim Pharunyou Chanthorn Rajendran Samidurai Chemistry Computer Science Mathematics © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Stochastic disturbances often cause undesirable characteristics in real-world system modeling. As a result, investigations on stochastic disturbances in neural network (NN) modeling are important. In this study, stochastic disturbances are considered for the formulation of a new class of NN models; i.e., the discrete-time stochastic quaternion-valued neural networks (DSQVNNs). In addition, the mean-square asymptotic stability issue in DSQVNNs is studied. Firstly, we decompose the original DSQVNN model into four real-valued models using the real-imaginary separation method, in order to avoid difficulties caused by non-commutative quaternion multiplication. Secondly, some new sufficient conditions for the mean-square asymptotic stability criterion with respect to the considered DSQVNN model are obtained via the linear matrix inequality (LMI) approach, based on the Lyapunov functional and stochastic analysis. Finally, examples are presented to ascertain the usefulness of the obtained theoretical results. 2020-10-14T08:29:01Z 2020-10-14T08:29:01Z 2020-06-01 Journal 20738994 2-s2.0-85087451157 10.3390/SYM12060936 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087451157&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70392
institution Chiang Mai University
building Chiang Mai University Library
continent Asia
country Thailand
Thailand
content_provider Chiang Mai University Library
collection CMU Intellectual Repository
topic Chemistry
Computer Science
Mathematics
spellingShingle Chemistry
Computer Science
Mathematics
Ramalingam Sriraman
Grienggrai Rajchakit
Chee Peng Lim
Pharunyou Chanthorn
Rajendran Samidurai
Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
description © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Stochastic disturbances often cause undesirable characteristics in real-world system modeling. As a result, investigations on stochastic disturbances in neural network (NN) modeling are important. In this study, stochastic disturbances are considered for the formulation of a new class of NN models; i.e., the discrete-time stochastic quaternion-valued neural networks (DSQVNNs). In addition, the mean-square asymptotic stability issue in DSQVNNs is studied. Firstly, we decompose the original DSQVNN model into four real-valued models using the real-imaginary separation method, in order to avoid difficulties caused by non-commutative quaternion multiplication. Secondly, some new sufficient conditions for the mean-square asymptotic stability criterion with respect to the considered DSQVNN model are obtained via the linear matrix inequality (LMI) approach, based on the Lyapunov functional and stochastic analysis. Finally, examples are presented to ascertain the usefulness of the obtained theoretical results.
format Journal
author Ramalingam Sriraman
Grienggrai Rajchakit
Chee Peng Lim
Pharunyou Chanthorn
Rajendran Samidurai
author_facet Ramalingam Sriraman
Grienggrai Rajchakit
Chee Peng Lim
Pharunyou Chanthorn
Rajendran Samidurai
author_sort Ramalingam Sriraman
title Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
title_short Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
title_full Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
title_fullStr Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
title_full_unstemmed Discrete-time stochastic quaternion-valued neural networks with time delays: An asymptotic stability analysis
title_sort discrete-time stochastic quaternion-valued neural networks with time delays: an asymptotic stability analysis
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087451157&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70392
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