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International Symposium on Neural Networks

ISNN 2010: Advances in Neural Networks - ISNN 2010 pp 627–634Cite as

Multistability Analysis: High-Order Networks Do Not Imply Greater Storage Capacity Than First-Order Ones

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6063))

Abstract

This paper presents new multistability of the networks with high-order interconnection. We construct invariant regions and establish new criteria of coexistence of equilibria which are exponentially stable. Our results show that high-order interactions of neurons may have lower storage capacity than first-order ones. Numerical simulations will illustrate our new and interesting results.

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Author information

Authors and Affiliations

  1. School of Sciences, Jimei University, Xiamen, 361021, P.R. China

    Zhenkun Huang

Authors
  1. Zhenkun Huang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Liqing Zhang

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu

  3. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water bay, Kowloon, Hong Kong, China

    James Kwok

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Huang, Z. (2010). Multistability Analysis: High-Order Networks Do Not Imply Greater Storage Capacity Than First-Order Ones. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13278-0_80

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  • DOI: https://doi.org/10.1007/978-3-642-13278-0_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13277-3

  • Online ISBN: 978-3-642-13278-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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