Event‐triggered H∞$\mathcal {H}_\infty$ synchronization of directed and switched coupled stochastic delayed neural networks with multi‐weights
Shanrong Lin, Xiwei Liu, Yanli Huang · IET Control Theory and Applications · 2022
Abstract This essay is devoted to studying synchronization problem of directed and switched coupled stochastic delayed neural networks with multi‐weights (SCSDNNMWs) via designing a novel event‐triggered protocol. The proposed model is based on stochastic delayed neural network with directed coupling, and multiple coupling matrices with switching express intricate and changing communication channels. Since the external disturbances are likely to cause network topologies change, fixed and accurate values of coupling matrices are difficult to obtain, while the above model has more advantages of characterizing this real network. Besides, zero eigenvalue of different coupling matrices are represented by the corresponding normalized left eigenvectors (NLEVec), which is hard to establish yet especially when designing necessary Lyapunov functions. The authors' essay deduces that if the Chebyshev distance among NLEVec of multiple coupling matrices is less than a permissible deviation limit based on a weighted set of these NLEVec, then several event‐triggered synchronization and synchronization criteria are established. The effectiveness of these results are verified by several given examples.