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Complex Dynamics in a Simple Hopfield-Type Neural Network

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

In this paper, we demonstrate complex dynamics in a classical Hopfield-type neural network with three neurons. There are no interconnections between the first one and the third one, so it may be a part with ignorable input from a complex neural network. However, the stable points, limit circles, single-scroll chaotic attractors and double-scrolls chaotic attractor have been observed as we adjust the weight from the second neuron to itself.

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Author information

Authors and Affiliations

  1. Institute for Nonlinear Systems, Chongqing University of Posts and Telecomm., Chongqing, 400065, China

    Qingdu Li & Xiaosong Yang

  2. Department of Mathematics, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiaosong Yang

Authors
  1. Qingdu Li
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  2. Xiaosong Yang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, Q., Yang, X. (2005). Complex Dynamics in a Simple Hopfield-Type Neural Network. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_56

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  • DOI: https://doi.org/10.1007/11427391_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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