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Compressive sensing.

Booth, Joshua Dennis.

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Compressive sensing.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Compressive sensing./
作者:	Booth, Joshua Dennis.
面頁冊數:	65 p.
附註:	Source: Masters Abstracts International, Volume: 49-02, page: 1212.
Contained By:	Masters Abstracts International49-02.
標題:	Applied Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1483097
ISBN:	9781124344942

Compressive sensing.
Booth, Joshua Dennis.

Compressive sensing. - 65 p.

Source: Masters Abstracts International, Volume: 49-02, page: 1212.

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

This work is an expository overview of certain key elements in the area of compressive sensing. As a sub-discipline of signal processing, compressive sensing is concerned with both sampling and reconstruction techniques. In this expository, sampling will center on random matrices and expander graphs, while reconstruction will use multiple numerical optimization techniques. Although theoretical performance bounds for these techniques can be found scattered throughout the published literature, there are few practical rules for concrete problems. This thesis helps fill this gap by experimenting on the asymptotic bounds of the number of measurements needed to guarantee perfect reconstruction. These numerical experiments help to identify specific sensing regimes in which performance begin to break down.

ISBN: 9781124344942Subjects--Topical Terms:

1669109
Applied Mathematics.

Compressive sensing.
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520 $a This work is an expository overview of certain key elements in the area of compressive sensing. As a sub-discipline of signal processing, compressive sensing is concerned with both sampling and reconstruction techniques. In this expository, sampling will center on random matrices and expander graphs, while reconstruction will use multiple numerical optimization techniques. Although theoretical performance bounds for these techniques can be found scattered throughout the published literature, there are few practical rules for concrete problems. This thesis helps fill this gap by experimenting on the asymptotic bounds of the number of measurements needed to guarantee perfect reconstruction. These numerical experiments help to identify specific sensing regimes in which performance begin to break down.
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