A delayed neural network for solving linear projection equations and its analysis.
In this paper, we present a delayed neural network approach to solve linear projection equations. The Lyapunov-Krasovskii theory for functional differential equations and the linear matrix inequality (LMI) approach are employed to analyze the global asymptotic stability and global exponential stability of the delayed neural network. Compared with the existing linear projection neural network, theoretical results and illustrative examples show that the delayed neural network can effectively solve a class of linear projection equations and some quadratic programming problems.
Liu
Qingshan
Q
Department of Mathematics, Southeast University, Nanjing 210096, China.
Cao
Jinde
J
Xia
Youshen
Y
D000465:Algorithms; D003198:Computer Simulation; D003205:Computing Methodologies; D016014:Linear Models; D008954:Models, Biological; D016571:Neural Networks, Computer; D009716:Numerical Analysis, Computer-Assisted; D011382:Programming, Linear; D013997:Time Factors