DocumentCode :
3269206
Title :
Using neural net architectures in analog circuits
Author :
Brooke, Martin A.
Author_Institution :
Duke Univ., Durham
fYear :
2007
fDate :
5-8 Aug. 2007
Firstpage :
1018
Lastpage :
1021
Abstract :
A method of using parallel analog building blocks with adjustable parameters was demonstrated to be able to achieve a wide array of analog circuit functionally with high accuracy. The method is generally useful when the penalty for needing to adapt the circuit to achieve performance is out weighted by the advantages in speed and power dissipation achievable by reducing the design constraints on the parallel building blocks which need not be very predictable.
Keywords :
analogue circuits; neural net architecture; adjustable parameters; analog circuits; design constraints; neural net architecture; parallel analog building blocks; Analog circuits; Application software; Circuit simulation; Computer architecture; EPROM; Feeds; Multi-layer neural network; Neural networks; Temperature; USA Councils;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2007. MWSCAS 2007. 50th Midwest Symposium on
Conference_Location :
Montreal, Que.
ISSN :
1548-3746
Print_ISBN :
978-1-4244-1175-7
Electronic_ISBN :
1548-3746
Type :
conf
DOI :
10.1109/MWSCAS.2007.4488735
Filename :
4488735
Link To Document :
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