Synchronization of Coupled Neutral-Type Neural Networks With Jumping-Mode-Dependent Discrete and Unbounded Distributed Delays

Abstract

Abstract-In this paper, the synchronization problem is studied for an array of N identical delayed neutral-type neural networks with Markovian jumping parameters. The coupled networks involve both the mode-dependent discrete time-delays and the mode-dependent unbounded distributed time-delays. All the network parameters including the coupling matrix are also dependent on the Markovian jumping mode. By introducing novel Lyapunov-Krasovskii functionals and using some analytical techniques, sufficient conditions are derived to guarantee that the coupled networks are asymptotically synchronized in mean square. The derived sufficient conditions are closely related with the discrete time-delays, distributed time-delays, mode transition probability and coupling structure of the networks. The obtained criteria are given in terms of matrix inequalities that can be solved efficiently by employing the semi-definite programme method. Numerical simulations are presented to further demonstrate the effectiveness of the proposed approach.

Synchronization of coupled neural networks with infinite-time distributed delays via quantized intermittent pinning control

“…It should be noted that existing intermittent control literatures, including [28]- [31], only consider bounded mixed delays. Another kind of delay called infinite-time distributed delay usually exists in NNs and cannot be ignored [32]- [34]. The authors in [32] investigated pth moment exponential synchronization of reaction-diffusion neural networks with discrete and infinitetime distributed delays under impulsive control.…”

“…Global finite-time synchronization of CNNs with both time-varying discrete delay and infinite-time distributed delay was studied in [33] by using state feedback control. In [34], the synchronization of neutral-type CNNs with infinitetime distributed delay was studied. However, to the best of our knowledge, there are few results on the synchronization of CNNs with infinite-time distributed delay via intermittent control.…”

Consensus of nonlinear multiagent systems with mode‐dependent delay via stochastic sampled data under Markovian switching topologies

“…In addition, it is considered that influenced by many complex environmental factors or internal mechanism of the system, the system model and the communication topology are not stationary. In this article, a continuous‐time and discrete‐state Markovian process $$$ r(t) $$$ is employed to describe the time‐varying delay of state in the nonlinear term and the process of the topology switching as numerous References 12–21. Suppose that the Markovian chain $$$ r(t) $$$ is right continuous and takes values in a finite space $$$ {\mathcal{I}}_{\tau } $$$.…”

“…There is no doubt that the topology switching is very complex in real world. Afterwards, many researchers devote themselves to dealing with more general switching mode, for example Markovian switching 12–22 . In the case, each switched topology has a random dwell time, which obeys exponential distribution.…”

An evolutionary deep neural network for predicting morbidity of gastrointestinal infections by food contamination

“…Moreover, due to the limitation of environment monitoring and data acquisition, the input can be imprecise and with much noise. For such a prediction problem, the classical feed-forward ANN with a single hidden layer often suffers from the issues of premature convergence and overfitting [26][27][28][29][30][31].…”