Global dissipativity of high-order Hopfield bidirectional associative memory neural networks with mixed delays
Author | Aouiti C. |
Author | Sakthivel R. |
Author | Touati F. |
Available date | 2022-05-22T11:03:03Z |
Publication Date | 2020 |
Publication Name | Neural Computing and Applications |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1007/s00521-019-04552-8 |
Abstract | In 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. |
Language | en |
Publisher | Springer |
Subject | Associative 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 |
Type | Article |
Pagination | 10183-10197 |
Issue Number | 14 |
Volume Number | 32 |
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