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 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...

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...

In this paper, the problem of stability analysis for a class of impulsive Cohen-Grossberg neural networks with mixed time delays is considered. The mixed time delays comprise both the time-varying and distributed delays. By employing a combination of the M -matrix theory and analytic methods, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium po...

In this paper, the problem of stability analysis for a class of impulsive stochastic Cohen-Grossberg neural networks with mixed delays is considered. The mixed time delays comprise both the time-varying and infinite distributed delays. By employing a combination of the M -matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and...

In this paper, we introduce the notion of stability sets for reaction-diffusion Cohen–Grossberg neural networks with time-varying delays. The Lyapunov–Razumikhin technique and a comparison principle are adapted to prove new criteria. addition, obtained results extended uncertain case, robust is also investigated. Examples considered demonstrate effectiveness our results.

Lewis proposes a "reconceptualization" (p. 1) of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for over thirty years. This commentary summarizes some of these themes and points to areas of particularly active research in this area. CO...

in this paper, we investigate the delay-dependent robust stability of fuzzy cohen-grossberg neural networks with markovian jumping parameter and mixed time varying delays by delay decomposition method. a new lyapunov-krasovskii functional (lkf) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matr...