• DocumentCode
    1808278
  • Title

    An information theoretic method for designing multiresolution principal component transforms

  • Author

    Jahromi, Omid S. ; Francis, Bruce A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada
  • Volume
    2
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    921
  • Abstract
    In signal processing, multiresolution transforms are used to decompose a time signal into components of different resolutions. In this paper, we consider designing optimal multiresolution transforms such that components in each resolution provide the best approximation to the original signal in that resolution. We call a transformation that admits this optimality property a principal component multiresolution transform (PCMT). We show that PCMTs can be designed by minimizing the information transfer through their basic building blocks. We then propose a method to do the minimization in a stage-by-stage manner. This latter method has a great appeal in terms of its computational simplicity as well as theoretical interpretations. In particular, it agrees with Linsker´s principle of self organization. Finally, we provide analytic arguments and computer simulations to demonstrate the efficiency of our method
  • Keywords
    information theory; minimisation; principal component analysis; signal processing; stochastic processes; transforms; Linsker principle; information theory; minimization; principal component analysis; principal component multiresolution transform; signal processing; stochastic process; Data compression; Design methodology; Filter bank; Information theory; Optimal control; Principal component analysis; Random variables; Signal processing; Signal resolution; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.831076
  • Filename
    831076