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Mean Square Stability in the Numerical Simulation of Stochastic Delayed Hopfield Neural Networks with Markovian Switching

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Advances in Neural Networks - ISNN 2010 (ISNN 2010)

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

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Abstract

This paper is concerned with the mean square stability for stochastic delayed Hopfield neural networks with Markovian switching. The sufficient conditions to guarantee the exponential stability in mean square of an equilibrium solution are given. Moreover, we give the mean square stability of the numerical method. The result shows that the numerical method shares the stability of the true solution.

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References

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Author information

Authors and Affiliations

  1. Department of Mathematics and Physics, Wuhan Polytechnic University, Wuhan, 430023, China

    Hua Yang & Jiangrong Liu

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

    Feng Jiang

Authors
  1. Hua Yang
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  2. Feng Jiang
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  3. Jiangrong Liu
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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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Yang, H., Jiang, F., Liu, J. (2010). Mean Square Stability in the Numerical Simulation of Stochastic Delayed Hopfield Neural Networks with Markovian Switching. 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_74

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  • DOI: https://doi.org/10.1007/978-3-642-13278-0_74

  • 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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