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Exponential Attractor of -Almost Periodic Sequence Solution of Discrete-time Bidirectional Neural Networks by Zhenkun Huang; Xinghua Wang; Yonghui Xia is a Engineering article available to read on EtoBox.

What is Exponential Attractor of -Almost Periodic Sequence Solution of Discrete-time Bidirectional Neural Networks about?

In this paper, several criteria are obtained for the existence and exponential attractivity of a unique j-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 j affects dynamical characteristics of bidirectional neural networks and our results on j-almost periodic sequence solution lead to effective estimates of continuous-time neural networks during real-time computations.

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Author

Zhenkun Huang; Xinghua Wang; Yonghui Xia

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 1569-190X)

Published

2010

Language

EN

Field

Engineering (Physical Sciences)