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author:

Huang, Zhenkun (Huang, Zhenkun.) [1] | Wang, Xinghua (Wang, Xinghua.) [2] | Xia, Yonghui (Xia, Yonghui.) [3]

Indexed by:

EI

Abstract:

In this paper, several criteria are obtained for the existence and exponential attractivity of a unique κ-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 κ affects dynamical characteristics of bidirectional neural networks and our results on κ-almost periodic sequence solution lead to effective estimates of continuous-time neural networks during real-time computations. © 2009 Elsevier B.V. All rights reserved.

Keyword:

Continuous time systems Neural networks

Community:

  • [ 1 ] [Huang, Zhenkun]School of Sciences, Jimei University, Xiamen, 361021, China
  • [ 2 ] [Wang, Xinghua]Department of Mathematics, Zhejiang University, Hangzhou, 310027, China
  • [ 3 ] [Xia, Yonghui]Department of Mathematics, Fuzhou University, Fuzhou, 350002, China

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Source :

Simulation Modelling Practice and Theory

ISSN: 1569-190X

Year: 2010

Issue: 3

Volume: 18

Page: 317-337

0 . 7 3 6

JCR@2010

3 . 5 0 0

JCR@2023

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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