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AuthorAouiti C.
AuthorSakthivel R.
AuthorTouati F.
Available date2022-05-22T11:03:03Z
Publication Date2020
Publication NameNeural Computing and Applications
ResourceScopus
Identifierhttp://dx.doi.org/10.1007/s00521-019-04552-8
URIhttp://hdl.handle.net/10576/31410
AbstractIn this paper, the problem of the global dissipativity of high-order Hopfield bidirectional associative memory neural networks with time-varying coefficients and distributed delays is discussed. By using Lyapunov?Krasovskii functional method, inequality techniques and linear matrix inequalities, a novel set of sufficient conditions for global dissipativity and global exponential dissipativity for the addressed system is developed. Further, the estimations of the positive invariant set, globally attractive set and globally exponentially attractive set are found. Finally, two examples with numerical simulations are provided to support the feasibility of the theoretical findings.
Languageen
PublisherSpringer
SubjectAssociative processing
Associative storage
Linear matrix inequalities
Memory architecture
Nonlinear control systems
Time varying networks
Dissipativity
Distributed delays
Global dissipativity
High-order neural network
Time varying- delays
Hopfield neural networks
TitleGlobal dissipativity of high-order Hopfield bidirectional associative memory neural networks with mixed delays
TypeArticle
Pagination10183-10197
Issue Number14
Volume Number32
dc.accessType Abstract Only


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