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Equilibrium Points and Stability Analysis of a Class of Neural Networks

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Advances in Neural Networks – ISNN 2007 (ISNN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4491))

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Abstract

This paper discusses a mathematical model of network, which is more general than the cellular neural networks(CNNs). In this study, we discuss some dynamical properties of this type of network, such as the distribution of equilibrium points and the influence of external input on stability. Moreover, we give some criterions, which ensure the complete stability of this network.

This work was supported by the national natural science fund of grant(10571035).

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References

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Author information

Authors and Affiliations

  1. Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China

    Xiaoping Xue

Authors
  1. Xiaoping Xue
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering (M/C 154), University of Illinois at Chicago, 851 S. Morgan Street, 60607-7053, Chicago, IL, USA

    Derong Liu

  2. School of Automation, Southeast University, 210096, Nanjing, China

    Shumin Fei

  3. Laboratory of Complex Systems, Institute of Automation, Chinese Adacemy of Sciences, 100080, Beijing, P. R. China

    Zeng-Guang Hou

  4. School of Information Science and Engineering, Northeast University, Shenyang, 110004, China

    Huaguang Zhang

  5. School of Electrical Engineering, Hohai University, Nanjing, 210098, China

    Changyin Sun

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© 2007 Springer-Verlag Berlin Heidelberg

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Xue, X. (2007). Equilibrium Points and Stability Analysis of a Class of Neural Networks. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_102

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  • DOI: https://doi.org/10.1007/978-3-540-72383-7_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72382-0

  • Online ISBN: 978-3-540-72383-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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