• DocumentCode
    2331875
  • Title

    An Explicit Construction Of A Reproducing Gaussian Kernel Hilbert Space

  • Author

    Xu, Jian-Wu ; Pokharel, Puskal P. ; Jeong, Kyu-Hwa ; Principe, Jose C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL
  • Volume
    5
  • fYear
    2006
  • fDate
    14-19 May 2006
  • Abstract
    In this paper, we propose a method to explicitly construct a reproducing kernel Hilbert space (RKHS) associated with a Gaussian kernel by means of polynomial spaces. In contrast to the conventional Mercer´s theorem approach that implicitly defines kernels by an eigendecomposition, the functionals in this reproducing kernel Hilbert space are explicitly constructed and are not necessary orthonormal. We also point out an intriguing connection between this reproducing kernel Hilbert space and a generalized Fock space. We give an experimental result on approximation of the constructed kernel to a Gaussian kernel
  • Keywords
    Hilbert spaces; approximation theory; eigenvalues and eigenfunctions; learning (artificial intelligence); polynomials; Gaussian kernel Hilbert space; Mercer theorem; eigendecomposition; generalized Fock space; polynomial spaces; Buildings; Hilbert space; Independent component analysis; Kernel; Laboratories; Machine learning; Neural engineering; Polynomials; Principal component analysis; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • Conference_Location
    Toulouse
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1661340
  • Filename
    1661340