Reachable set estimation for Markovian jump neural networks with time-varying delay.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper is concerned with the reachable set estimation for Markovian jump neural networks with time-varying delay and bounded peak inputs. The objective is to find a description of a reachable set that is containing all reachable states starting from the origin. In the framework of Lyapunov-Krasovskii functional method, an appropriate Lyapunov-Krasovskii functional is constructed firstly. Then by using the Wirtinger-based integral inequality and the extended reciprocally convex matrix inequality, an ellipsoidal description of the reachable set for the considered neural networks is derived. Finally, a numerical example with simulation results is provided to verify the effectiveness of our results.

Authors

  • Wen-Juan Lin
    School of Automation, China University of Geosciences, Wuhan 430074, China; Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China.
  • Yong He
    College of Biosystems Engineering and Food Science, Zhejiang Univ., Hangzhou, 310058, China.
  • Min Wu
    Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
  • Qingping Liu
    Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China. liuqingping@gzucm.edu.cn.