In this article, we consider a model that describes the dynamics of Cohen-Grossberg neural networks with unbounded distributed delays, whose state variable are governed by stochastic non-linear integro-differential equations. Without assuming the smoothness, monotonicity and boundedness of the activation functions, by constructing suitable Lyapunov functional, employing the semi-martingale conv...

Cortical Dynamics of Navigation and Steering in Natural Scenes: Motion-Based Object Segmentation, Heading, and Obstacle Avoidance by N. Andrew Browning, Stephen Grossberg, Ennio Mingolla Department of Cognitive and Neural Systems, Center for Adaptive Systems and Center of Excellence for Learning in Education, Science and Technology Boston University, 677 Beacon Street, Boston, MA 02215 December...

A class of Cohen-Grossberg neural networks with distributed delays are considered. By using the coincidence degree theorem and differential inequality techniques, sufficient conditions for the existence and exponential stability of the periodic solutions are established, Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnec...

Abstract. In this paper, by using a continuation theorem of coincidence degree theory and a differential inequality, we establish some sufficient conditions ensuring the existence and global exponential stability of anti-periodic solutions for a class of fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays. In addition, we present an illustrative example to show the fe...

In this paper, we investigate a class of fuzzy CohenGrossberg neural networks with time delays and impulsive effects. By virtue of stochastic analysis, Halanay inequality for stochastic differential equations, we find sufficient conditions for the global exponential square-mean synchronization of the FCGNNs under noise perturbation. In particular, the traditional assumption on the differentiabi...

Ž . The paper presents two neural networks based on the adaptive resonance theory ART for the recognition of several odors subjected Ž . to drift. The neural networks developed by Grossberg supervised and unsupervised have been used for two different drift behaviors. One in which the clusters end up to overlap each other and the other when they do not. The latter case is solved by unsupervision...