Finite-time dissipative control for bidirectional associative memory neural networks with state-dependent switching and time-varying delays

Yang, J; Chen, G; Wen, S

Finite-time dissipative control for bidirectional associative memory neural networks with state-dependent switching and time-varying delays

Yang, J Chen, G Wen, S

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Knowledge-Based Systems, 2022, 252, pp. 109338
Issue Date:: 2022-09-27

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Field	Value	Language
dc.contributor.author	Yang, J
dc.contributor.author	Chen, G
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2023-02-28T03:29:02Z
dc.date.available	2023-02-28T03:29:02Z
dc.date.issued	2022-09-27
dc.identifier.citation	Knowledge-Based Systems, 2022, 252, pp. 109338
dc.identifier.issn	0950-7051
dc.identifier.uri	http://hdl.handle.net/10453/166517
dc.description.abstract	This paper focuses on finite-time exponential dissipative analysis and control problems for bidirectional associative memory neural networks (BAMNNs) with state-dependent switching and time-varying delays. Firstly, the state-dependent switching parameters of BAMNNs are interpreted as interval parameters by the interval matrix method instead of differential inclusion theory and set-value map. Under the framework of Filippov's solution and differential inclusions, some sufficient conditions of finite-time bounded (FTB) and finite-time exponential (Q,S,R)−γ dissipative (FTED) for BAMNNs are obtained based on Lyapunov–Krasovskii functional (LKF) and some inequality techniques. Then, the finite-time dissipative PI controllers are designed by solving linear matrix inequality (LMI). Finally, a numerical example is given to illustrate the correctness of the proposed results and the effectiveness of the designed controllers.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Knowledge-Based Systems
dc.relation.isbasedon	10.1016/j.knosys.2022.109338
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Finite-time dissipative control for bidirectional associative memory neural networks with state-dependent switching and time-varying delays
dc.type	Journal Article
utslib.citation.volume	252
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
dc.date.updated	2023-02-28T03:29:00Z
pubs.publication-status	Published
pubs.volume	252

Abstract:

This paper focuses on finite-time exponential dissipative analysis and control problems for bidirectional associative memory neural networks (BAMNNs) with state-dependent switching and time-varying delays. Firstly, the state-dependent switching parameters of BAMNNs are interpreted as interval parameters by the interval matrix method instead of differential inclusion theory and set-value map. Under the framework of Filippov's solution and differential inclusions, some sufficient conditions of finite-time bounded (FTB) and finite-time exponential (Q,S,R)−γ dissipative (FTED) for BAMNNs are obtained based on Lyapunov–Krasovskii functional (LKF) and some inequality techniques. Then, the finite-time dissipative PI controllers are designed by solving linear matrix inequality (LMI). Finally, a numerical example is given to illustrate the correctness of the proposed results and the effectiveness of the designed controllers.

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http://hdl.handle.net/10453/166517