Sampling theory in a general reproducing kernel Hilbert space = 일반적인 reproducing kernel 힐버트 공간에서의 샘플링 이론

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Sampling procedure consists of the reduction of an analog signal into a digital signal and the reconstruction of the original signal from its discrete values. Starting from the classical WSK theorem, various extensions in sampling theory have been developed and widely applied in signal processing and information theory. This dissertation handles the sampling expansions in a general reproducing kernel Hilbert space. We begin by introducing engineering approach of WSK theorem in a Paley-wiener space. Then we describe the general sampling theorem in a reproducing kernel Hilbert space setting which is a subspace of $L^2(\mathbb{R})$ closed in a particular sobolev space and develop the theorems with more general conditions. Secondly, we deal with a construction of a reproducing kernel Hilbert space which admits a stable sampling set and characterize its properties. Finally we draw sampling expansions in the constructed space.
Advisors
Kwon, Kil-Hyunresearcher권길헌researcher
Description
한국과학기술원 : 수리과학과,
Publisher
한국과학기술원
Issue Date
2011
Identifier
467725/325007  / 020093093
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 수리과학과, 2011.2, [ iii, 21 p. ]

Keywords

sampling theory; reproducing kernel; Shannon`s sampling; 샘플링 이론; 샤논; generalized sampling theorem

URI
http://hdl.handle.net/10203/181625
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=467725&flag=dissertation
Appears in Collection
MA-Theses_Master(석사논문)
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