In this article, the chance-constrained state estimation problem is investigated for a class of
time-varying neural networks subject to measurements degradation and randomly occurring …

Recently, the dynamical behaviors of coupled neural networks (CNNs) with and without
reaction-diffusion terms have been widely researched due to their successful applications in …

The problem of asynchronous and resilient filtering for discrete-time Markov jump neural
networks subject to extended dissipativity is investigated in this paper. The modes of the …

In this paper, two multiple weighted coupled reaction-diffusion neural networks (CRDNNs)
with and without coupling delays are introduced. On the one hand, some finitetime passivity …

A novel generalized neural network (NN), which includes Markovian jump parameters,
inertial items, and reaction-diffusion terms, is proposed, and the issue of finite-time …

This paper discusses the passivity of delayed reaction–diffusion memristor-based neural
networks (RDMNNs). By exploiting inequality techniques and by constructing appropriate …

This paper respectively studies finite-time passivity of multi-weighted coupled neural
networks (MWCNNs) with and without coupling delays. First, based on those existing …

In this paper, the non-fragile dissipative state estimation is addressed for semi-Markov jump
inertial neural networks with reaction-diffusion. A semi-Markov jump model is used to …

This paper presents a complex network model consisting of N uncertain reaction-diffusion
neural networks with multiple time delays. We analyze the passivity and synchronization of …

This paper mainly discusses the passivity and synchronization for a coupled neural
networks with multi-weights (CNNMWs) by virtue of devised proportional-integral-derivative …