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

• Published in: IEEE transactions on cybernetics Vol. 52; no. 7; pp. 6591 - 6602
• Main Authors: Shen, Hao, Huang, Zhengguo, Wu, Zhengguang, Cao, Jinde, Park, Ju H.
• Format: Journal Article
• Language: English
• Published: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.07.2022
• Subjects: Acclimatization; Associative memory; Convexity; Decoupling method; Dwell time; Neural networks; Optimization; Synchronism; Systems theory; Time synchronization
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2021.3119199

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.