Nonfragile H ∞ Synchronization of BAM Inertial Neural Networks Subject to Persistent Dwell-Time Switching Regularity

This article concentrates on the synchronization of discrete-time persistent dwell-time (PDT) switched bidirectional associative memory inertial neural networks with time-varying delays. Through the use of the switched system theory related to the PDT, the convex optimization technique together with...

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Vydáno v:IEEE transactions on cybernetics Ročník 52; číslo 7; s. 6591 - 6602
Hlavní autoři: Shen, Hao, Huang, Zhengguo, Wu, Zhengguang, Cao, Jinde, Park, Ju H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.07.2022
Témata:
Acclimatization
Associative memory
Convexity
Decoupling method
Dwell time
Neural networks
Optimization
Synchronism
Systems theory
Time synchronization
ISSN:2168-2267, 2168-2275, 2168-2275
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Shrnutí:This article concentrates on the synchronization of discrete-time persistent dwell-time (PDT) switched bidirectional associative memory inertial neural networks with time-varying delays. Through the use of the switched system theory related to the PDT, the convex optimization technique together with some straightforward decoupling methods, an appropriate mode-dependent controller with nonfragility is developed to acclimatize itself to some practical circumstances. Simultaneously, sufficient conditions of ensuring the [Formula Omitted] performance and exponential stability for the resulting switched synchronization error system are derived. Finally, a numerical example is utilized to show the validity of the model constructed and the influence of the PDT on the [Formula Omitted] performance. In addition, an image encryption example is employed to show the potential application prospect of the investigated system.
Bibliografie:ObjectType-Article-1
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2021.3119199