In this paper we give a sufficient condition to imply local and global asymptotic attractivity of the equilibrium of the Cohen-Grossberg neural network with time-dependent delays of the form ẋi(t) = ci(x(t)) 

ABSTRACT. We study impulsive Cohen-Grossberg neural networks with S-type distributed delays. This type of delays in the presence of impulses is more general than the usual types of delays studied in the literature. Using analysis techniques we prove the existence of a unique equilibrium point. By means of simple and efficient Lyapunov functions we present some sufficient conditions for the expo...

and Applied Analysis 3 see 35 . When designing an associative memory neural network, we should make convergence speed as high as possible to ensure the quick convergence of the network operation. Therefore, pth moment p ≥ 2 exponential stability and almost sure exponential stability are most useful concepts as they imply that the solutions will tend to the trivial solution exponentially fast. T...

ABSTRACT. In this paper, the robust exponential stability problem is investigated for a class of uncertain Markovian jumping stochastic Cohen-Grossberg type bidirectional associative memory neural networks (CGBAMNN) with time-varying delays and reaction-diffusion terms. By using the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guarante...

To the best of our knowledge, there are only few results on general decay stability applied to stochastic neural networks. In the paper, we study both the pth moment ðpZ2Þ and the almost sure stability on a general decay rate for impulsive stochastic Cohen–Grossberg neural networks with mixed time delays. The presented theory allows us to study the pth moment stability even if the exponential s...

In this paper, we investigate the almost periodic dynamical behaviors for a class of general Cohen–Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and nonsmooth analysis theory with generalized Lyapunov approach, we obtain the existence, uniqueness and global stability of almost periodic solu...

In this paper, we consider the convergence dynamics of Cohen–Grossberg neural networks (CGNNs) with continuously distributed delays. Without assuming the differentiability and monotonicity of activation functions, the differentiability of amplification functions and the symmetry of synaptic interconnection weights, we construct suitable Lyapunov functionals and employ inequality technique to es...

The existence and global asymptotic stability of a large class of Cohen-Grossberg neural networks is discussed in this paper. Previous papers always assume that the amplification function has positive lower and upper bounds, which excludes a large class of functions. In our paper, it is only needed that the amplification function is positive. Also, the model discussed is general, the method use...