DocumentCode
2663729
Title
Programmable SC neural networks for solving nonlinear programming problems
Author
Jou, I. Chang ; Wu, Chung-Yu ; Liu, Ron-Yi
Author_Institution
Minist. of Commun., Chung-Li, Taiwan
fYear
1990
fDate
1-3 May 1990
Firstpage
2837
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
Keywords
VLSI; analogue computer circuits; neural nets; nonlinear programming; switched capacitor networks; SC neural networks; VLSI implementation; discrete-time neural network; nonlinear programming problems; online solution; programmability; switched-capacitor; Circuit simulation; Computer architecture; Linear programming; Neural networks; Quadratic programming; Resistors; Switched capacitor circuits; Switching circuits; Symmetric matrices; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location
New Orleans, LA
Type
conf
DOI
10.1109/ISCAS.1990.112601
Filename
112601
Link To Document