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Neural Processing Letters
Published in: Neural Processing Letters 6/2021

11-08-2021

Stability and Hopf Bifurcation Analysis of a General Tri-diagonal BAM Neural Network with Delays

Authors: Tianshun Wang, Yu Wang, Zunshui Cheng

Published in: Neural Processing Letters | Issue 6/2021

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Abstract

In this article, a general tri-diagonal bidirectional associative memory (BAM) neural network model with 2n-neurons is proposed. Our investigates have some distinct superiorities, including forward transmission delay and feedback delay in the model are considered. Moreover, the neural network model considered with 2n-neurons is more general in application. We obtain the general expression of characteristic equation of BAM neural network model with 2n-neurons for investigating its stability and Hopf bifurcation. The distribution characteristics of roots of characteristic equation are discussed in detail to get the sufficient conditions for Hopf bifurcation of system caused by delays. Then the designed protocol is simpler and easier to implement compared with some previously investigates. Subsequently, by using the normal form method and central manifold theorem, the direction of Hopf bifurcation and the period and stability of bifurcation periodic solution are determined. Finally, several examples are also utilized to illustrate the validity of theoretical results.
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Metadata
Title
Stability and Hopf Bifurcation Analysis of a General Tri-diagonal BAM Neural Network with Delays
Authors
Tianshun Wang
Yu Wang
Zunshui Cheng
Publication date
11-08-2021
Publisher
Springer US
Published in
Neural Processing Letters / Issue 6/2021
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-021-10613-8

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