• 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