%0 Journal Article
%T Wavelets adapted to compact domains in reproducing kernel Hilbert spaces
%A D. W. Struble
%J Applied Mathematical Sciences
%D 2013
%I 
%X Reproducing kernel Hilbert spaces and wavelets are both mathemat-ical tools used in system identication and approximation. Reproducingkernel Hilbert spaces are function spaces possessing special characteris-tics that facilitate the search for solutions to norm minimization prob-lems [3]. As such, they are of interest in a variety of areas includingMachine Learning [11]. Wavelets are another modeling tool used forfunction approximation and analysis. They are desirable due to theirmultiscale feature, localization in time and frequency, and fast decom-position / reconstruction algorithms. In this work we merge waveletsadapted to compact domains [10] with reproducing kernel Hilbert spacesfollowing the construction developed by R. Opfer [6]. We provide re-sults for the representation, multiscale nature, and decomposition / reconstruction algorithms for approximations arising from the multiscale reproducing kernel Hilbert spaces.
%K Wavelet
%K Compact
%K Domain
%K Reproducing
%K Kernel
%K Hilbert
%K Space
%K multiscale
%K multiresolution
%K Machine
%K Learning
%U http://www.m-hikari.com/ams/ams-2013/ams-17-20-2013/strubleAMS17-20-2013.pdf