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Global asymptotic synchronisation of fuzzy inertial neural networks with time-varying delays by applying maximum-value approach

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In the paper, we are concerned about the global asymptotic synchronisation for a class of fuzzy master–slave inertial neural networks with time-varying delays. At present, most of the research on… Click to show full abstract

In the paper, we are concerned about the global asymptotic synchronisation for a class of fuzzy master–slave inertial neural networks with time-varying delays. At present, most of the research on the global asymptotic synchronisation of fuzzy master–slave inertial neural networks with time-varying delays adopt the matrix measure method, linear matrix inequality approach and integral inequality method. While in our paper, we attain three criteria to assure the global asymptotic synchronisation between the master system and the slave system by designing three classes of different novel controllers via the maximum-value analysis approach. The controllers designed and the maximum-value method used in this paper are completely novel compared with these in the existing literatures, which enrich and extend the published results.

Keywords: neural networks; asymptotic synchronisation; inertial neural; networks time; global asymptotic

Journal Title: International Journal of Systems Science
Year Published: 2022

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