Abstract

A Reproducing Kernel Hilbert Space (RKHS) is first of all a Hilbert space, that is, the most natural extension of the mathematical model for the actual space where everyday life takes place (the Euclidean space ℝ3). When studying elements of some abstract set S it is convenient to consider them as elements of some other set S′ on which is already defined a structure relevant to the problem to be treated. It can be for instance an order structure, a vector structure, a metric structure or a mixing of algebraic and topological structures. For this we need an “imbedding theorem” or a “representation theorem”. Through this kind of theorem the study of elements of S is transferred to their “representers” in S′ and can be carried out using the structure on S′. For their richness and simplicity Hilbert spaces are introduced as often as possible when a vector structure and an inner product can be exploited. They provide powerful mathematical tools and geometric concepts on which our intuition can rest. The phrase “RKHS method” is generic to name a method based on the embedding of the abstract set S into some RKHS S′.

Keywords

Hilbert Space Cauchy Sequence Separable Hilbert Space Reproduce Kernel Hilbert Space Orthonormal System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Alain Berlinet
    • 1
  • Christine Thomas-Agnan
    • 2
  1. 1.Department of Mathematics, UMR CNRS 5030University of Montpellier IIMontpellier cedex 05France
  2. 2.GREMAQ, UMR CNRS 5604University of Toulouse IToulouseFrance

Personalised recommendations