DocumentCode :
2617632
Title :
Obtaining high precision operation from nonideal neural networks
Author :
Sculley, Terry L. ; Brooke, Martin A.
Author_Institution :
Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
1990
fDate :
1-3 May 1990
Firstpage :
1847
Abstract :
Several potential neural architectures for an A/D converter are examined, and the level of nonidealities that can be tolerated by the network components without inhibiting high-precision operation through training is discussed. Behavioral-level simulations on sample converter networks with modeled nonidealities revealed a strong interrelationship between the network architectures and their tolerance to nonidealities
Keywords :
analogue-digital conversion; learning systems; neural nets; A/D converter; behavioural-level simulations; high precision operation; modeled nonidealities; network components; neural architectures; nonideal neural networks; sample converter networks; training; Circuit stability; Computational modeling; Computer architecture; Computer networks; Feedback circuits; Integrated circuit interconnections; Multilayer perceptrons; Neural networks; Pipelines; Telephony;
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.1990.112018
Filename :
112018
Link To Document :
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