Boundedness and Stability for Discrete‐Time Delayed Neural Network with Complex‐Valued Linear Threshold Neurons

Abstract

The discrete‐time delayed neural network with complex‐valued linear threshold neurons is considered. By constructing appropriate Lyapunov‐Krasovskii functionals and employing linear matrix inequality technique and analysis method, several new delay‐dependent criteria for checking the boundedness and global exponential stability are established. Illustrated examples are also given to show the effectiveness and less conservatism of the proposed criteria.