DocumentCode :
1456500
Title :
Analog Implementation of a Novel Resistive-Type Sigmoidal Neuron
Author :
Khodabandehloo, Golnar ; Mirhassani, Mitra ; Ahmadi, Majid
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
Volume :
20
Issue :
4
fYear :
2012
fDate :
4/1/2012 12:00:00 AM
Firstpage :
750
Lastpage :
754
Abstract :
An important part of any hardware implementation of artificial neural networks (ANNs) is realization of the activation function which serves as the output stage of each layer. In this work, a new NMOS/PMOS design is proposed for realizing the sigmoid function as the activation function. Transistors in the proposed neuron are biased using only one biasing voltage. By operating in both triode and saturation regions, the proposed neuron can provide an accurate approximation of the sigmoid function. The neuron circuit is designed and laid out in 90-nm CMOS technology. The proposed neuron can be potentially used in implementation of both analog and hybrid ANNs.
Keywords :
CMOS analogue integrated circuits; MOSFET; neural chips; neural nets; triodes; CMOS technology; NMOS-PMOS design; activation function; artificial neural networks; biasing voltage; resistive-type sigmoidal neuron circuit; saturation regions; size 90 nm; triode; Approximation methods; Artificial neural networks; Equations; Mathematical model; Neurons; Transistors; Very large scale integration; Activation function; analog neuron; sigmoid function; sigmoidal neuron;
fLanguage :
English
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-8210
Type :
jour
DOI :
10.1109/TVLSI.2011.2109404
Filename :
5719144
Link To Document :
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