Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
837504 | Nonlinear Analysis: Real World Applications | 2012 | 6 Pages |
Abstract
This paper investigates ultimate boundedness and a weak attractor for stochastic Hopfield neural networks (HNN) with time-varying delays. By employing the Lyapunov method and the matrix technique, some novel results and criteria on ultimate boundedness and an attractor for stochastic HNN with time-varying delays are derived. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results.
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Authors
Li Wan, Qinghua Zhou, Pei Wang, Jizi Li,