Programmable SC neural networks for solving nonlinear programming problems

I. Chang Jou*, Chung-Yu Wu, Ron Yi Liu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

Neural networks for the online solution of linear and nonlinear programming problems are presented. Adopting switched-capacitor (SC) techniques, the proposed circuits have the advantages of VLSI implementation and programmability. Simulation results show the stability and availability of the discrete-time neural network. The optimum solutions are obtained in near real time.

Original languageEnglish
Pages (from-to)2837-2840
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume4
DOIs
StatePublished - 1 Dec 1990
Event1990 IEEE International Symposium on Circuits and Systems Part 4 (of 4) - New Orleans, LA, USA
Duration: 1 May 19903 May 1990

Fingerprint Dive into the research topics of 'Programmable SC neural networks for solving nonlinear programming problems'. Together they form a unique fingerprint.

Cite this