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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...
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| Главные авторы: | , , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Taylor & Francis Group
2018-01-01
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| Серии: | Systems Science & Control Engineering |
| Предметы: | |
| Online-ссылка: | http://dx.doi.org/10.1080/21642583.2018.1544512 |
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