DocumentCode
3329595
Title
Programmable non-linearity for neural networks applications
Author
Sargeni, Fausto ; Bonaiuto, Vincenzo
Author_Institution
Dept. of Electron. Eng., Univ. of Rome Tor Vergata, Rome, Italy
fYear
2009
fDate
2-5 Aug. 2009
Firstpage
881
Lastpage
884
Abstract
The implementation of analogue circuits for modeling Artificial Neural Networks as well as Neuromorphic architectures, makes wide use of nonlinear circuits where the programmability feature could be a very interesting characteristic. This paper deals with the design of a "current-mode" digitally programmable transconductance comparator. In particular, it has been properly tailored for a "time-division architecture" implementation of a first order STAR CNN system.
Keywords
analogue circuits; comparators (circuits); current-mode circuits; neural nets; nonlinear network synthesis; analogue circuits; artificial neural networks; current-mode transconductance amplifier; digitally programmable transconductance comparator; first order STAR CNN system; neuromorphic architectures; nonlinear circuits; programmable nonlinearity; time-division architecture; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2009. MWSCAS '09. 52nd IEEE International Midwest Symposium on
Conference_Location
Cancun
ISSN
1548-3746
Print_ISBN
978-1-4244-4479-3
Electronic_ISBN
1548-3746
Type
conf
DOI
10.1109/MWSCAS.2009.5235907
Filename
5235907
Link To Document