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A delay-dividing approach to robust stability of uncertain stochastic complex-valued Hopfield delayed neural networks

Chanthorn, Pharunyou, Rajchakit, Grienggrai, Humphries, Usa, Kaewmesri, Pramet, Sriraman, Ramalingam and Lim, Chee Peng 2020, A delay-dividing approach to robust stability of uncertain stochastic complex-valued Hopfield delayed neural networks, Symmetry, vol. 12, no. 5, pp. 1-19, doi: 10.3390/SYM12050683.

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Title A delay-dividing approach to robust stability of uncertain stochastic complex-valued Hopfield delayed neural networks
Author(s) Chanthorn, Pharunyou
Rajchakit, Grienggrai
Humphries, Usa
Kaewmesri, Pramet
Sriraman, Ramalingam
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name Symmetry
Volume number 12
Issue number 5
Article ID 683
Start page 1
End page 19
Total pages 19
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2020-04-25
ISSN 2073-8994
Keyword(s) complex-valued Hopfield neural networks
robust stability
parameter uncertainties
stochastic effects
Summary In scientific disciplines and other engineering applications, most of the systems refer to uncertainties, because when modeling physical systems the uncertain parameters are unavoidable. In view of this, it is important to investigate dynamical systems with uncertain parameters. In the present study, a delay-dividing approach is devised to study the robust stability issue of uncertain neural networks. Specifically, the uncertain stochastic complex-valued Hopfield neural network (USCVHNN) with time delay is investigated. Here, the uncertainties of the system parameters are norm-bounded. Based on the Lyapunov mathematical approach and homeomorphism principle, the sufficient conditions for the global asymptotic stability of USCVHNN are derived. To perform this derivation, we divide a complex-valued neural network (CVNN) into two parts, namely real and imaginary, using the delay-dividing approach. All the criteria are expressed by exploiting the linear matrix inequalities (LMIs). Based on two examples, we obtain good theoretical results that ascertain the usefulness of the proposed delay-dividing approach for the USCVHNN model.
Language eng
DOI 10.3390/SYM12050683
Indigenous content off
Copyright notice ©2020, the authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30138782

Document type: Journal Article
Collections: Institute for Frontier Materials
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.