The global exponential stability is investigated for a class of generalized Cohen–Grossberg neural networks with discrete delays. By means of the combination of the nonlinear measure approach and constructing a novel Lyapunov functional together with some nonlinear functional analysis and inequality techniques, general sufficient conditions are obtained for the existence, uniqueness and global ...

For a family of differential equations with infinite delay, we give sufficient conditions for the global asymptotic, and global exponential stability of an equilibrium point. This family includes most of the delayed models of neural networks of Cohen-Grossberg type, with both bounded and unbounded distributed delay, for which general asymptotic and exponential stability criteria are derived. As...

In this paper, the exponential stability of periodic solutions for inertial Cohen-Grossberg-type neural networks are investigated. First, by properly chosen variable substitution the system is transformed to first order differential equation. Second, some sufficient conditions which can ensure the existence and exponential stability of periodic solutions for the system are obtained by using con...

Impulsive Cohen-Grossberg neural networks with bounded and unbounded delays i.e., mixed delays are investigated. By using the Leray-Schauder fixed point theorem, differential inequality techniques, and constructing suitable Lyapunov functional, several new sufficient conditions on the existence and global exponential stability of periodic solution for the system are obtained, which improves som...

Abstract: The paper is concerned with the existence and global exponential stability of periodic solutions for inertial Cohen-Grossberg-type BAM neural networks with time delays. With variable transformation the system is transformed to first order differential equations. Some new sufficient conditions ensuring the existence and global exponential stability of periodic solutions for the system ...

The stability for the switched Cohen-Grossberg neural networks with mixed time delays and αinverse Hölder activation functions is investigated under the switching rule with the average dwell time property. By applying multiple Lyapunov-Krasovskii functional approach and linear matrix inequality LMI technique, a delay-dependent sufficient criterion is achieved to ensure such switched neural netw...

Abstract. In this paper, the finite-time synchronization problem for chaotic Cohen–Grossberg neural networks with unknown parameters and time-varying delays is investigated by using finitetime stability theory. Firstly, based on the parameter identification of uncertain delayed neural networks, a simple and effective feedback control scheme is proposed to tackle the unknown parameters of the ad...