• DocumentCode
    1471692
  • Title

    A scalable low voltage analog Gaussian radial basis circuit

  • Author

    Theogarajan, Luke ; Akers, L.A.

  • Author_Institution
    Center for Solid State Electron. Res., Arizona State Univ., Tempe, AZ, USA
  • Volume
    44
  • Issue
    11
  • fYear
    1997
  • fDate
    11/1/1997 12:00:00 AM
  • Firstpage
    977
  • Lastpage
    979
  • Abstract
    Gaussian basis function (GBF) networks are powerful systems for learning and approximating complex input-output mappings. Networks composed of these localized receptive field units trained with efficient learning algorithms have been simulated solving a variety of interesting problems. For real-time and portable applications however, direct hardware implementation is needed. We describe experimental results from the most compact, low voltage analog Gaussian basis circuit yet reported. We also extend our circuit to handle large fan-in with minimal additional hardware. Our design is hierarchical and the number of transistors scales almost linearly with the input dimension making it amenable to VLSI implementation
  • Keywords
    CMOS analogue integrated circuits; VLSI; analogue processing circuits; neural chips; Gaussian basis function networks; VLSI implementation; analog Gaussian radial basis circuit; hardware implementation; hierarchical design; large fan-in; learning algorithms; localized receptive field units; scalable low voltage analog circuit; Application software; Biological neural networks; Circuit simulation; Computer vision; Detectors; Hardware; Input variables; Low voltage; Neurons; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7130
  • Type

    jour

  • DOI
    10.1109/82.644055
  • Filename
    644055