A delayed neural network for solving linear projection equations and its analysis

Qingshan Liu; Jinde Cao; Youshen Xia

doi:10.1109/TNN.2005.849834

A delayed neural network for solving linear projection equations and its analysis

IEEE Trans Neural Netw. 2005 Jul;16(4):834-43. doi: 10.1109/TNN.2005.849834.

Authors

Qingshan Liu¹, Jinde Cao, Youshen Xia

Affiliation

¹ Department of Mathematics, Southeast University, Nanjing 210096, China.

PMID: 16121725
DOI: 10.1109/TNN.2005.849834

Abstract

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.

Publication types

Evaluation Study
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Computer Simulation
Computing Methodologies
Linear Models*
Models, Biological*
Neural Networks, Computer*
Numerical Analysis, Computer-Assisted
Programming, Linear*
Time Factors