Finite-Time Stability for Delayed Complex-Valued BAM Neural Networks

摘要

This paper studies the finite-time stability problem of complex-valued BAM neural networks with time delay. Firstly, based on a more suitable assumption for the complex-valued activation functions of the considered system, a tractable entire real-valued system is formed. Using nonlinear measure approach, a condition to ensure the existence and uniqueness of the equilibrium point for this system is derived. Then, a finite-time stability criterion of the equilibrium point is obtained in terms of LMIs by Lyapunov function approach. In the end, simulation examples are provided to verify the validity and advantages of the proposed conditions.