GLOBAL DISSIPATIVITY OF POSITIVE NEURAL NETWORKS WITH TIME-VARYING DELAYS

DOI: 10.18173/2354-1059.2025-0018

Abstract

In this paper, the problems of positivity and dissipativity are investigated for a model of neural networks with time-varying delays. A novel approach based on comparison techniques via differential and integral inequalities is presented and utilized to derive testable conditions which ensure the existence and the global dissipativity of a unique positive equilibrium point. The derived conditions are formulated in terms of linear programming with M-matrix, providing a computationally efficient framework for analysis. A numerical example with simulations is provided to illustrate the theoretical results and demonstrate their practical applicability