Mean Square Exponential Stability of Hybrid Neural Networks with Uncertain Switching Probabilities

  • Xuyang Lou
  • Qian Ye
  • Ke Lou
  • Baotong Cui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7390)


This paper is concerned with the global exponential stability problem for a class of Markovian jumping recurrent neural networks (MJRNNs) with uncertain switching probabilities. The Markovian jumping recurrent neural networks under consideration involve parameter uncertainties in the mode transition rate matrix. By employing a Lyapunov functional, a linear matrix inequality (LMI) approach is developed to establish an easy-totest and delay-independent sufficient condition which guarantees that the dynamics of the neural network is globally exponentially stable in the mean square.


Hybrid neural networks Markovian jumping exponential stability 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xuyang Lou
    • 1
  • Qian Ye
    • 1
  • Ke Lou
    • 1
  • Baotong Cui
    • 1
  1. 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education)Jiangnan UniversityWuxiChina

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