Recurrent neural network for solving quadratic programming problems with equality constraints

J. Wang

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

A recurrent neural network for solving quadratic programming problems with equality constraints is presented. The proposed recurrent neural network is asymptotically stable and able to generate optimal solutions to quadratic programs with equality constraints. An opamp based analogue circuit realisation of the recurrent neural network is described. An illustrative example is also discussed to demonstrate the performance and characteristics of the analogue neural network.

Original languageEnglish
Pages (from-to)1345-1347
Number of pages3
JournalElectronics Letters
Volume28
Issue number14
DOIs
Publication statusPublished - 2 Jul 1992
Externally publishedYes

Keywords

  • Neural networks

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