4.5 Article

Global Exponential Synchronization of Complex-Valued Neural Networks with Time Delays via Matrix Measure Method

期刊

NEURAL PROCESSING LETTERS
卷 49, 期 1, 页码 187-201

出版社

SPRINGER
DOI: 10.1007/s11063-018-9805-9

关键词

Complex-valued neural networks; Global exponential synchronization; Matrix measure; Halanay inequality; Time delays

资金

  1. National Natural Science Foundation of China [11371126]
  2. High School Outstanding Young Support Plan of Anhui Province [gxyq2014175]
  3. Natural Science Research Project of Anhui Province [KJ2015A347, KJ2017A704]
  4. Key Project of Natural Science Research of Bozhou University [BYZ2017B03]

向作者/读者索取更多资源

In this paper, global exponential synchronization of a class of complex-valued neural networks with time delays is investigated. Based on Halanay inequality theory, Lyapunov theory and matrix measure method, by separating complex-valued neural networks to the real part and imaginary part, several criteria for the global exponentially synchronization of complex-valued neural networks are presented. Finally, one numerical simulation is given to show the effectiveness of our theoretical results.

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