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New result on the mean-square exponential input-to-state stability of stochastic delayed recurrent neural networks

In this paper, we solve the mean-square exponential input-to-state stability problem for a class of stochastic delayed recurrent neural networks with time-varying coefficients. With the aid of stochastic analysis theory and a Lyapunov-Krasovskii functional, we derive a novel criterion that ensures t...

詳細記述

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書誌詳細
主要な著者: Wentao Wang, Shuhua Gong, Wei Chen
フォーマット: Artigo
言語:Inglês
出版事項: Taylor & Francis Group 2018-01-01
シリーズ:Systems Science & Control Engineering
主題:
オンライン・アクセス:http://dx.doi.org/10.1080/21642583.2018.1544512
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