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Compressive sensing for wireless net...

Han, Zhu, (1974-)

Compressive sensing for wireless networks

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Compressive sensing for wireless networksby Zhu Han, Husheng Li, Wotao Yin.
作者:	Han, Zhu,
其他作者:	Li, Husheng,
出版者:	Cambridge :Cambridge University Press,2013.
面頁冊數:	xiv, 293 p. :ill., digital ;26 cm.
標題:	Coding theory.
電子資源:	https://doi.org/10.1017/CBO9781139088497
ISBN:	9781139088497$q(electronic bk.)

Compressive sensing for wireless networks
Han, Zhu,1974-

Compressive sensing for wireless networks[electronic resource] /by Zhu Han, Husheng Li, Wotao Yin. - Cambridge :Cambridge University Press,2013. - xiv, 293 p. :ill., digital ;26 cm.

Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and limitations, and the skills needed to take advantage of compressive sensing in wireless networks.

ISBN: 9781139088497$q(electronic bk.)Subjects--Topical Terms:

184605
Coding theory.

LC Class. No.: TK5102.92 / .H355 2013

Dewey Class. No.: 621.3981

Compressive sensing for wireless networks
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520 $a Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and limitations, and the skills needed to take advantage of compressive sensing in wireless networks.
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