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International Symposium on Neural Networks

ISNN 2013: Advances in Neural Networks – ISNN 2013 pp 109–116Cite as

Bifurcation of a Discrete-Time Cohen-Grossberg-Type BAM Neural Network with Delays

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7951)

Abstract

A tri-neuron discrete-time Cohen-Grossberg BAM neural network with delays is investigated in this paper. By analyzing the corresponding characteristic equations, the asymptotical stability of the null solution and the existence of Neimark-Sacker bifurcations are discussed. By applying the normal form theory and the center manifold theorem, the direction of the Neimark-Sacker bifurcation and the stability of bifurcating periodic solutions are obtained. Numerical simulations are given to illustrate the obtained results.

Keywords

  • Cohen-Grossberg neural network
  • discrete time
  • delay
  • stability
  • Neimark-Sacker bifurcation

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Author information

Authors and Affiliations

  1. Institute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, Shijiazhuang, 050003, China

    Qiming Liu

Authors
  1. Qiming Liu
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Editor information

Editors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, A 530, Chuangxinyuan Building, 116023, Dalian, China

    Chengan Guo

  2. Institute of Automation, Chinese Academy of Sciences, 100864, Beijing, China

    Zeng-Guang Hou

  3. School of Automation, Huazhong University of Science and Technology, 430074, Wuhan, China

    Zhigang Zeng

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Liu, Q. (2013). Bifurcation of a Discrete-Time Cohen-Grossberg-Type BAM Neural Network with Delays. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39065-4_14

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  • DOI: https://doi.org/10.1007/978-3-642-39065-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39064-7

  • Online ISBN: 978-3-642-39065-4

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