Synchronization in Quaternion-Valued Neural Networks with Delay and Stochastic Impulses

Chengsheng Li, Jinde Cao, Ardak Kashkynbayev

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A class of global exponential synchronization problem for delayed quaternion-valued neural networks with stochastic impulses has been investigated in this paper, where the impulses arouse time and strength both are randomly. Firstly, the delayed quaternion-valued model with stochastic impulses was fain to separate to four real-valued parts in consideration of the fact that noncommutativity character of quaternion multiplication. Then, a new criterion was obtained to achieve the global exponential synchronization via building an appropriate classically Lyapunov candidate function and utilizing the method of comparison principle and reduction to absurdity. Finally, in order to verify the validity of the proposed theorem, a given numerical example is provided.

Original languageEnglish
Pages (from-to)691-708
Number of pages18
JournalNeural Processing Letters
Volume54
Issue number1
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Delayed quaternion-valued neural network
  • Global exponential synchronization
  • Stochastic impulses

ASJC Scopus subject areas

  • Software
  • General Neuroscience
  • Computer Networks and Communications
  • Artificial Intelligence

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