DocumentCode
2883953
Title
An artificial neural-based A/D converter using asymmetric Hopfield network
Author
Ning, Zhang ; Junli, Zheng
Author_Institution
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
fYear
1991
fDate
16-17 Jun 1991
Firstpage
66
Abstract
The properties of local minima in the energy function of the Tank A/D converter network are studied in detail, and a new design of neural-based A/D converters using asymmetrically connected Hopfield networks has been developed, which can eliminate these local minima completely. The simulated results using SPICE agree well with theoretical analysis of the asymmetric A/D converter
Keywords
analogue-digital conversion; circuit analysis computing; convergence; neural nets; nonlinear network analysis; SPICE; Tank A/D converter; asymmetric Hopfield network; energy function local minima; neural-based A/D converter; optimal convergence; simulated results; Analog-digital conversion; Artificial neural networks; Circuit simulation; Computational modeling; Computer networks; Neural networks; SPICE; Speech recognition; Very large scale integration; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1991. Conference Proceedings, China., 1991 International Conference on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/CICCAS.1991.184282
Filename
184282
Link To Document