Abstract: The global exponential stability is investigated for a class of reaction-diffusion Cohen-Grossberg-type BAM neural networks with time delays. By constructing suitable Lyapunov functional and using homeomorphism mapping, several sufficient conditions guaranteeing the existence, uniqueness and global exponential stability of reaction-diffusion Cohen-Grossberg-type BAM neural networks wi...

In this paper, a generalized reaction-diffusion model of Cohen Grossberg neural networks with time-varying and distributed delays is investigated. By employing analytic methods, inequality technique and M -matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for Cohen-Grossberg neural networks with time-varying and di...

Based on the theory of calculus on time scales, the homeomorphism theory, Lyapunov functional method, and some analysis techniques, sufficient conditions are obtained for the existence, uniqueness, and global exponential stability of the equilibrium point of Cohen-Grossberg bidirectional associative memory BAM neural networks with distributed delays and impulses on time scales. This is the firs...

In this paper, the global asymptotic stability of second-order neutral type Cohen-Grossberg neural networks with time-varying delays are investigated. First, by choosing properly variable substitution the system is transformed to first-order differential equation. Second, some sufficient conditions which can ensure the existence and global asymptotic stability of equilibrium point for the syste...

In this brief, robust adaptive control of unknown modified Cohen–Grossberg neural networks with time delays is considered based on nonsmooth analysis and matrix inequality technique. Several new controllers are designed to ensure the global asymptotical stability of the targeted equilibrium point. The designed controllers are independent of the bounds of the perturbations, system functions and ...

This paper is concerned with finite-time synchronization for a class of delayed neural networks with Cohen–Grossberg type. Different from the existing related results, the time-delayed feedback strategy is utilized to investigate finite-time synchronization of delayed Cohen–Grossberg neural networks. By constructing Lyapunov functions and using differential inequalities, several new and effecti...

This article analyzes exponential synchronization for a class of Cohen-Grossberg neural networks with time-varying delays. Firstly, according to the concept synchronization, controlled response system is constructed, and error obtained. Secondly, by establishing suitable Lyapunov functions using inequality techniques, sufficient conditions under different controllers are provided, convergence r...

In this paper, we discuss dynamics of Cohen–Grossberg neural networks with discontinuous activations functions. We provide a relax set of sufficient conditions based on the concept of Lyapunov diagonally stability (LDS) for Cohen–Grossberg networks to be absolutely stable. Moreover, under certain conditions we prove that the system is exponentially stable globally or convergent globally in fini...

This paper mainly deals with the almost surely exponential stability and exponential p-th moment stability for a class of stochastic Cohen–Grossberg neural networks with distributed delays and reaction–diffusion term. By constructing suitable Lyapunov functional, employing the nonnegative semi-martingale convergence theorem and applying matrix theory and stochastic analysis technique, two delay...