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Sparse representation for detection ...

Sieger, Caroline Marguerite.

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Sparse representation for detection of transients using a multi-resolution representation of the auto-correlation of wavelets.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Sparse representation for detection of transients using a multi-resolution representation of the auto-correlation of wavelets./
作者:	Sieger, Caroline Marguerite.
面頁冊數:	139 p.
附註:	Source: Masters Abstracts International, Volume: 48-05, page: 3033.
Contained By:	Masters Abstracts International48-05.
標題:	Applied Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1475572
ISBN:	9781109747881

Sparse representation for detection of transients using a multi-resolution representation of the auto-correlation of wavelets.
Sieger, Caroline Marguerite.

Sparse representation for detection of transients using a multi-resolution representation of the auto-correlation of wavelets. - 139 p.

Source: Masters Abstracts International, Volume: 48-05, page: 3033.

Thesis (M.S.)--Clemson University, 2010.

This thesis seeks to detect damped sinusoidal transients, specifically capacitor switching transients, buried in noise and to answer the following questions: (1) Can the transient s(t; q) be sparsely represented from sdelta( t) = s(t; q)+epsilon(t) using sparsity methods, where epsilon(t) is white Gaussian noise? (2) Does computing the local auto-correlation of the signal around the transient improve detection? (3) How does the auto-correlation shell representation compare to the wavelet representation? (4) Which basis is "best"? (5) Which method and representation is best? This thesis explores detection schemes based on classical methods and newer sparsity methods. Classical methods considered include reconstruction via wavelets and reconstruction in the novel multi-resolution representation based on the autocorrelation functions of compactly supported wavelets. For simplicity, only four bases are considered: Haar, Daubechies 2, Daubechies 4, and Symlets 2. Sparsity methods include the iterative soft, hard, and combined thresholding algorithms.

ISBN: 9781109747881Subjects--Topical Terms:

1669109
Applied Mathematics.

Sparse representation for detection of transients using a multi-resolution representation of the auto-correlation of wavelets.
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