Hostname: page-component-7b7567c8c-fvjsw Total loading time: 0 Render date: 2026-11-14T11:08:24.433Z Has data issue: false hasContentIssue false

Sampling analysis in the complex reproducing kernel Hilbert space1

Published online by Cambridge University Press:  21 November 2014

BING-ZHAO LI*
Affiliation:
School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China, 100081Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China, 100081
QING-HUA JI
Affiliation:
School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China, 100081
*
*Corresponding Email: li_bingzhao@bit.edu.cn
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

We consider and analyse sampling theories in the reproducing kernel Hilbert space (RKHS) in this paper. The reconstruction of a function in an RKHS from a given set of sampling points and the reproducing kernel of the RKHS is discussed. Firstly, we analyse and give the optimal approximation of any function belonging to the RKHS in detail. Then, a necessary and sufficient condition to perfectly reconstruct the function in the corresponding RKHS of complex-valued functions is investigated. Based on the derived results, another proof of the sampling theorem in the linear canonical transform (LCT) domain is given. Finally, the optimal approximation of any band-limited function in the LCT domain from infinite sampling points is also analysed and discussed.

Information

Type
Papers
Copyright
Copyright © Cambridge University Press 2014