Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
492965 | Simulation Modelling Practice and Theory | 2010 | 21 Pages |
Abstract
In this paper, several criteria are obtained for the existence and exponential attractivity of a unique κκ-almost periodic sequence solution of discrete-time bidirectional neural networks (BNNs). Our results generalize the corresponding results about almost periodic sequence solution in common sense. Finally, computer simulations illustrate the dynamic behavior of discrete-time bidirectional neural networks. It is shown that discretization step κκ affects dynamical characteristics of bidirectional neural networks and our results on κκ-almost periodic sequence solution lead to effective estimates of continuous-time neural networks during real-time computations.
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Zhenkun Huang, Xinghua Wang, Yonghui Xia,