Adaptive Resonance Theory (ART) models arc real-lime neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP networks synthesize fuzzy logic and ART by exploiting the formal similarity between tile computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable ...

<p style='text-indent:20px;'>This research paper deals with the investigation of global robust stability results for Cohen-Grossberg neural networks involving multiple constant time delays. The activation functions in this network model are supposed to be set non-decreasing slope-bounded nonlinear and uncertainties parameters considered have bounded upper norms. By employing a proper posi...

A discrete-time analogue is formulated for an impulsive Cohen-Grossberg neural network with transmission delay in a manner in which the global exponential stability characterisitics of a unique equilibrium point of the network are preserved. The formulation is based on extending the existing semidiscretization method that has been implemented for computer simulations of neural networks with lin...

In this paper, a new spiking neural network architecture based Ellias Grossberg model is proposed and different connection schemes that investigate the synchronization performance is provided. The synchronization time and the network neurons correlation are used as a measure of the network performance. An example of a pattern recognition problem is used to illustrate the proposed connection sch...

We consider a class of systems of differential equations in R which exhibits convergent dynamics. We find a Lyapunov function and show that every bounded trajectory converges to the set of equilibria. Our result generalizes the results of Cohen and Grossberg [1] for convergent neural networks. It replaces the symmetry assumption on the matrix of weights by the assumption on the structure of the...

In this paper, we study the nonnegative periodic dynamics of the delayed Cohen–Grossberg neural networks with discontinuous activation functions and periodic interconnection coefficients, selfinhibitions, and external inputs. Filippov theory is utilized to study the viability, namely, the existence of the solution of the Cauchy problem. Under some conditions, the existence and the asymptotical ...

The impulsive control method is developed to stabilize a class of Cohen–Grossberg neural networks (CGNNs) with reaction–diffusion terms and Dirichlet boundary conditions. With the help of Lyapunov functionals, impulsive delay differential inequality and comparison principle, some sufficient conditions ensuring global exponential stability (GES) of equilibrium point are obtained. In particular, ...