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Exponential Stability of Neural Network with General Noise

  • Xin Zhang
  • Yiyuan Zheng
  • Yiming Gan
  • Wuneng Zhou
  • Yuqing Sun
  • Lifei Yang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 528)

Abstract

The problem of exponential stability of neural network (NN) with general noise is considered in this article. The noise in our neural network model which can be a mixture of white and non-white noise is more suitable for real nervous systems than white noise. By utilizing the random analysis method and Lyapunov functional method techniques, we obtain the conditions of the exponential stability for neural network with general noise. Unlike the NN with white noise in the existing papers, which are modeled as stochastic differential equations, our model with general noise is based on the random differential equations. Finally, an illustrative example is presented to demonstrate the effectiveness and usefulness of the proposed results.

Keywords

Exponential stability Neural networks General noise 

Notes

Acknowledgements

This work was partially supported by the Natural Science Foundation of China (grant no. 61573095).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xin Zhang
    • 1
  • Yiyuan Zheng
    • 2
  • Yiming Gan
    • 1
    • 3
  • Wuneng Zhou
    • 1
  • Yuqing Sun
    • 1
  • Lifei Yang
    • 4
  1. 1.School of Information Science and TechnologyDonghua UniversityShanghaiChina
  2. 2.Wenlan School of BusinessZhongnan University of Economics and LawWuhanChina
  3. 3.Bros Eastern Stock Co., Ltd. NingboChina
  4. 4.Glorious Sun School of Business and ManagementDonghua UniversityShanghaiChina

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