• DocumentCode
    2229464
  • Title

    Subspace estimation by hierarchical neural PCA: analog/digital implementation constraints

  • Author

    Paraschiv-Ionescu, Ani ; Jutten, C. ; Bouvier, G.

  • Author_Institution
    INPGrenoble, France
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    742
  • Abstract
    This paper addresses the issue of hardware implementation of hierarchical neural principal component analysis (PCA). We attempt to show by experimental studies the effect of finite accuracy computations on the algorithm´s performance, for both analog and digital implementation
  • Keywords
    array signal processing; eigenvalues and eigenfunctions; learning (artificial intelligence); neural nets; principal component analysis; analog/digital implementation constraints; finite accuracy computations; hardware implementation; hierarchical neural PCA; principal component analysis; subspace estimation; Algorithm design and analysis; Eigenvalues and eigenfunctions; Electronics packaging; Hardware; Neural networks; Physics computing; Principal component analysis; Sensor arrays; Signal processing algorithms; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
  • Conference_Location
    Geneva
  • Print_ISBN
    0-7803-5482-6
  • Type

    conf

  • DOI
    10.1109/ISCAS.2000.856167
  • Filename
    856167
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2229464