Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks with Probabilistic Time-Varying Delays

Meng Hui, Jiahuang Zhang, Jiao Zhang, Herbert Ho Ching Iu, Rui Yao, Lin Bai

Research output: Contribution to journalArticle

Abstract

This paper addresses finite-time projective synchronization of stochastic complex-valued neural networks (SCVNNs) with probabilistic time-varying delays (PTVs). First, in the complex domain, PTVs are introduced into the studied model and a novel feedback control scheme is constructed. Next, based on inequalities techniques and the Lyapunov stability approach, some novel projective synchronization criteria are established by decomposing SCVNNs into two equivalent real-valued systems. Moreover, a setting time function is created by employing lemma 4. Compared with previous researches, our theory content is an extension and complement to known results. Finally, numerical simulation is presented to validate the effectiveness of theoretical analysis results.

Original languageEnglish
Article number9380365
Pages (from-to)44784-44796
Number of pages13
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

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