A recurrent neural network with exponential convergence for solving convex quadratic program and related linear piecewise equations

Authors:
Youshen Xia;Gang Feng;Jun Wang
Affiliations:
Department of Manufacturing Engineering and Engineering Management, The City University of Hong Kong, Hong Kong, China and Department of Applied Mathematics, Nanjing University of Posts and Teleco ...;Department of Manufacturing Engineering and Engineering Management, The City University of Hong Kong, Hong Kong, China;Department of Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, China
Venue:
Neural Networks
Year:
2004

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Abstract

This paper presents a recurrent neural network for solving strict convex quadratic programming problems and related linear piecewise equations. Compared with the existing neural networks for quadratic program, the proposed neural network has a one-layer structure with a low model complexity. Moreover, the proposed neural network is shown to have a finite-time convergence and exponential convergence. Illustrative examples further show the good performance of the proposed neural network in real-time applications.