Stability in distribution of stochastic delay recurrent neural networks with Markovian switching

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• 作者：Enwen Zhu ; George Yin ; Quan Yuan
• 刊名：Neural Computing & Applications
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：27
• 期：7
• 页码：2141-2151
• 全文大小：551 KB
• 刊物类别：Computer Science
• 刊物主题：Simulation and Modeling
  
• 出版者：Springer London
• ISSN：1433-3058
• 卷排序：27

文摘

This paper investigates the stability in distribution of stochastic delay recurrent neural networks with Markovian switching. Using Lyapunov function and stochastic analysis techniques, sufficient conditions on the stability in distribution are given. For such recurrent neural networks, it reveals that the limit distribution of transition probability for segment process associated with solution process is indeed a unique ergodic invariant probability measure. Moreover, a numerical example is also provided to demonstrate the effectiveness and applicability of the theoretical results.KeywordsStability in distributionStochastic recurrent neural networkBrownian motionMarkov chain