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This paper is concerned with the global exponential dissipativity of memristive inertial neural networks with discrete and distributed time-varying delays. By constructing appropriate Lyapunov–Krasovskii functionals, some new sufficient conditions ensuring global exponential dissipativity of memristive inertial neural networks are derived. Moreover, the globally exponential attractive sets and positive invariant sets are also presented here. In addition, the new proposed results here complement and extend the earlier publications on conventional or memristive neural network dynamical systems. Finally, numerical simulations are given to illustrate the effectiveness of obtained results. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to discuss the neutral predator–prey model with Hassell–Varley type functional response and two time-varying delays. Some new sufficient conditions are obtained for the existence of positive periodic solutions by applying the coincidence degree theorem. Finally, numerical simulations are then carried out as supporting evidences of our analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we consider the global exponential stability in a Lagrange sense for memristive recurrent neural networks with time-varying delays. Here, we adopt nonsmooth analysis and control theory to handle memristive neural networks with discontinuous right-hand side, and by constructing proper Lyapunov functionals and using inequality technique, several new sufficient conditions in linear matrix inequality form are given to ensure the ultimate boundedness and global exponential attractivity of the memristor-based neural networks in the sense of Filippov solutions. In addition, these conditions do not require the connection weight matrices to be symmetric and the delay functions to be differentiable. Finally, numerical simulations illustrate the effectiveness of our results. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the exponential synchronization of coupled memristor-based chaotic neural networks with both time-varying delays and general activation functions. And here, we adopt nonsmooth analysis and control theory to handle memristor-based chaotic neural networks with discontinuous right-hand side. In particular, several new criteria ensuring exponential synchronization of two memristor-based chaotic neural networks are obtained via periodically intermittent control. In addition, the new proposed results here are very easy to verify and also complement, extend the earlier publications. Numerical simulations on the chaotic systems are presented to illustrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: This paper is concerned with the global exponential anti-synchronization of a class of chaotic memristive neural networks with time-varying delays. The dynamic analysis here employs results from the theory of differential equations with discontinuous right-hand side as introduced by Filippov. And by using differential inclusions theory, the Lyapunov functional method and the inequality technique, some new sufficient conditions ensuring exponential anti-synchronization of two chaotic delayed memristive neural networks are derived. The new proposed results here are very easy to verify and they also improve the earlier publications. Finally, a numerical example is given to illustrate the effectiveness of the new scheme. [Copyright &y& Elsevier]

Abstract: The paper analyzes a general memristor-based recurrent neural networks with time-varying delays (DRNNs). The dynamic analysis in the paper employs results from the theory of differential equations with discontinuous right-hand side as introduced by Filippov, and some new conditions concerning global exponential stability are obtained. In addition, these conditions do not require the activation functions to be differentiable, the connection weight matrices to be symmetric and the delay functions to be differentiable, our results are mild and more general. Finally, numerical simulations illustrate the effectiveness of our results. [Copyright &y& Elsevier]

The finite-time stabilization of discontinuous switched systems is a highly challenging problem. To address this problem, this article proposes a unified controller that achieves fixed-time and preassigned-time stabilization of discontinuous switched systems with time-varying delays, which is superior to finite-time stabilization. Compared with finite-time stabilization results, the settling time for fixed-time stabilization is independent of the initial state of the system. For preassigned-time stabilization, the settling time can be set in advance regardless of the initial state and controller parameters. Also, the fixed-time and preassigned-time stabilization methods proposed in this article are general and can be extended for applications to other nonlinear discontinuous systems with time delays. • A unified control framework is proposed to achieve both fixed-time and preassigned-time stabilization. • Achieve fixed-time stabilization of discontinuous switched systems and obtain more accurate settling times. • Different from finite-time stabilization, the settling time for fixed-time stabilization is independent of the initial state. • The settling time for preassigned-time stabilization can be set ready despite the initial state and controller parameters. [ABSTRACT FROM AUTHOR]