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Absolutely Exponential Stability of BAM Neural Networks with Distributed Delays

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Advances in Neural Networks – ISNN 2004 (ISNN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3173))

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Abstract

Some novel criteria are obtained for checking the absolute stability of the equilibrium point for bidirectional associative memory networks with distributed delays, where the activation functions only need to be partially Lipschitz continuous, but not bounded or differentiable.

This work was jointly supported by the National Natural Science Foundation of China, the Natural Science Foundation of Jiangsu Province, China.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Southeast University, Nanjing, 210096, China

    Wenjun Xiong & Qiuhao Jiang

  2. Department of Mathematics, China Pharmaceutical University, Nanjing, 210009, China

    Qiuhao Jiang

Authors
  1. Wenjun Xiong
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  2. Qiuhao Jiang
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Editor information

Editors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, China

    Fu-Liang Yin

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

    Jun Wang

  3. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, Liaoning, China

    Chengan Guo

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© 2004 Springer-Verlag Berlin Heidelberg

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Xiong, W., Jiang, Q. (2004). Absolutely Exponential Stability of BAM Neural Networks with Distributed Delays. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_19

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  • DOI: https://doi.org/10.1007/978-3-540-28647-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22841-7

  • Online ISBN: 978-3-540-28647-9

  • eBook Packages: Springer Book Archive

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