MATLAB Simulation and Comparison of Zhang Neural Network and Gradient Neural Network for Time-Varying Lyapunov Equation Solving

Authors:
Yunong Zhang;Shuai Yue;Ke Chen;Chenfu Yi
Affiliations:
Department of Electronics and Communication Engineering, ,;School of Software, Sun Yat-Sen University, Guangzhou, China 510275;School of Software, Sun Yat-Sen University, Guangzhou, China 510275;Department of Electronics and Communication Engineering, ,
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Year:
2008

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Abstract

This paper presents a new kind of recurrent neural network proposed by Zhang et al.for solving online Lyapunov equation with time-varying coefficient matrices. Global exponential convergence could be achieved by such a recurrent neural network when solving the time-varying problems in comparison with gradient neural networks (GNN). MATLAB simulation of both neural networks for the real-time solution of time-varying Lyapunov equation is then investigated through several important techniques. Computer-simulation results substantiate the theoretical analysis and demonstrate the efficacy of such a Zhang neural network (ZNN) on time-varying Lyapunov equation solving, especially when using power-sigmoid activation functions.