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Irregular sampling of wavelet transforms and reconstruction.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Irregular sampling of wavelet transforms and reconstruction./
作者:
Kicey, Charles John.
面頁冊數:
1 online resource (132 pages)
附註:
Source: Dissertations Abstracts International, Volume: 59-02, Section: B.
Contained By:
Dissertations Abstracts International59-02B.
標題:
Mathematics. -
電子資源:
click for full text (PQDT)
ISBN:
9780591358896
Irregular sampling of wavelet transforms and reconstruction.
Kicey, Charles John.
Irregular sampling of wavelet transforms and reconstruction.
- 1 online resource (132 pages)
Source: Dissertations Abstracts International, Volume: 59-02, Section: B.
Thesis (Ph.D.)--University of Pittsburgh, 1996.
Includes bibliographical references
We start by providing examples showing that although it is plausible that signals are characterized by their (infinite-scale) wavelet transform extrema, as conjectured by Mallat and Zhong, this is not the case even in a practical setting. Sampling wavelet transforms at extrema leads us to consider reconstruction from irregular sampling of wavelet transforms via alternating projections in Hilbert space. Here we develop some evidence indicating the importance of sampling at large values. We develop a very flexible finite-scale framework for which the reconstruction process will converge. From here, we then rigorously develop a discrete version of the algorithm and, when the wavelet generates an orthonormal multiresolution analysis, we gain a near complete understanding of the behavior of the algorithm for regular samplings. To finish, we consider band-limited wavelets, and show that under certain irregular sampling schemes we have unique reconstruction with a computable geometric rate of convergence. We improve on the original results for band-limited wavelets, gaining enough flexibility in our choice of samplings to develop a discrete version. Finally, we give an interesting application of wavelet theory that is not related to the main body of this dissertation.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9780591358896Subjects--Topical Terms:
527692
Mathematics.
Index Terms--Genre/Form:
554714
Electronic books.
Irregular sampling of wavelet transforms and reconstruction.
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Includes bibliographical references
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We start by providing examples showing that although it is plausible that signals are characterized by their (infinite-scale) wavelet transform extrema, as conjectured by Mallat and Zhong, this is not the case even in a practical setting. Sampling wavelet transforms at extrema leads us to consider reconstruction from irregular sampling of wavelet transforms via alternating projections in Hilbert space. Here we develop some evidence indicating the importance of sampling at large values. We develop a very flexible finite-scale framework for which the reconstruction process will converge. From here, we then rigorously develop a discrete version of the algorithm and, when the wavelet generates an orthonormal multiresolution analysis, we gain a near complete understanding of the behavior of the algorithm for regular samplings. To finish, we consider band-limited wavelets, and show that under certain irregular sampling schemes we have unique reconstruction with a computable geometric rate of convergence. We improve on the original results for band-limited wavelets, gaining enough flexibility in our choice of samplings to develop a discrete version. Finally, we give an interesting application of wavelet theory that is not related to the main body of this dissertation.
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click for full text (PQDT)
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