LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays

摘要

Discrete neural models are of great importance in numerical simulations and practical implementations. Inthe current paper, a discrete model of continuous-time neural networks with variable and distributed delaysis investigated. By Lyapunov stability theory and techniques such as linear matrix inequalities, sufficientconditions guaranteeing the existence and global exponential stability of the unique equilibrium point areobtained. Introduction of LMIs enables one to take into consideration the sign of connection weights. To showthe effectiveness of the method, an illustrative example, along with numerical simulation, is presented.