This paper focuses on the global exponential synchronization of multiple memristive reaction-diffusion neural networks (MRDNNs) with time delay. Due to introducing the influences of space as well as time on state variables and replacing resistors with memristors in circuit realization, the state-dependent partial differential mathematical model of MRDNN is more general and realistic than traditional neural network model. Based on Lyapunov functional theory, Divergence theorem and inequality techniques, global exponential synchronization criteria of coupled delayed MRDNNs are derived via directed and undirected nonlinear coupling. Finally, three numerical simulation examples are presented to verify the feasibility of our main results
This article is devoted to analyzing the finite-time and fixed-time synchronization of coupled memri...
This article investigates the global exponential stabilization (GES) of inertial memristive neural n...
In this paper, we investigate the exponential synchronization problem of memristive neural networks ...
This paper is concerned with the finite/fixed-time synchronization (FFTS) problems of two delayed me...
This paper investigated the global synchronization of fractional-order memristive neural networks (F...
© 2013 IEEE. This paper is concerned with the global exponential synchronization of two memristor-ba...
This paper studies the exponential anti-synchronization problem of memristive delayed neural network...
Abstract This paper deals with the global Mittag-Leffler synchronization of fractional-order memrist...
This paper addresses the global exponential dissipativity of memristor-based recurrent neural networ...
This paper presents a new impulsive synchronization criterion of two identical reaction-diffusion ne...
This paper investigates the global exponential synchronization and quasi-synchronization of inertial...
This paper concerns the problem of global exponential synchronization for a class of memristor-based...
In this paper, we further investigate the finite-/fixed-time synchronization (FFTS) problem for a cl...
This paper studies the general decay projective synchronization (GDPS) of a class of drive-response ...
The network models of multi-weighted coupled neural networks (MWCNNs) and multi-weighted coupled rea...
This article is devoted to analyzing the finite-time and fixed-time synchronization of coupled memri...
This article investigates the global exponential stabilization (GES) of inertial memristive neural n...
In this paper, we investigate the exponential synchronization problem of memristive neural networks ...
This paper is concerned with the finite/fixed-time synchronization (FFTS) problems of two delayed me...
This paper investigated the global synchronization of fractional-order memristive neural networks (F...
© 2013 IEEE. This paper is concerned with the global exponential synchronization of two memristor-ba...
This paper studies the exponential anti-synchronization problem of memristive delayed neural network...
Abstract This paper deals with the global Mittag-Leffler synchronization of fractional-order memrist...
This paper addresses the global exponential dissipativity of memristor-based recurrent neural networ...
This paper presents a new impulsive synchronization criterion of two identical reaction-diffusion ne...
This paper investigates the global exponential synchronization and quasi-synchronization of inertial...
This paper concerns the problem of global exponential synchronization for a class of memristor-based...
In this paper, we further investigate the finite-/fixed-time synchronization (FFTS) problem for a cl...
This paper studies the general decay projective synchronization (GDPS) of a class of drive-response ...
The network models of multi-weighted coupled neural networks (MWCNNs) and multi-weighted coupled rea...
This article is devoted to analyzing the finite-time and fixed-time synchronization of coupled memri...
This article investigates the global exponential stabilization (GES) of inertial memristive neural n...
In this paper, we investigate the exponential synchronization problem of memristive neural networks ...