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

Youshen Xia, Gang Feng, Jun Wang

Research output: Contribution to journalArticlepeer-review

153 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1003-1015
Number of pages13
JournalNeural Networks
Volume17
Issue number7
DOIs
Publication statusPublished - Sep 2004
Externally publishedYes

Keywords

  • Convex quadratic program
  • Exponential convergence
  • Finite-time convergence
  • Neural network
  • Piecewise equation

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