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Signal enhancement with variable spa...

Benesty, Jacob.

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Signal enhancement with variable span linear filters

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Signal enhancement with variable span linear filters/ by Jacob Benesty, Mads G. Christensen, Jesper R. Jensen.
作者:	Benesty, Jacob.
其他作者:	Christensen, Mads G.
出版者:	Singapore :Springer Singapore : : 2016.,
面頁冊數:	ix, 172 p. :ill., digital ;24 cm.
內容註:	Introduction -- General Concept with Filtering Vectors -- General Concept with Filtering Matrices -- Single-Channel Signal Enhancement in the STFT Domain -- Multichannel Signal Enhancement in the Time Domain -- Multichannel Signal Enhancement in the STFT Domain -- Binaural Signal Enhancement in the Time Domain.
Contained By:	Springer eBooks
標題:	Signal processing. -
電子資源:	http://dx.doi.org/10.1007/978-981-287-739-0
ISBN:	9789812877390$q(electronic bk.)

Signal enhancement with variable span linear filters
Benesty, Jacob.

Signal enhancement with variable span linear filters[electronic resource] /by Jacob Benesty, Mads G. Christensen, Jesper R. Jensen. - Singapore :Springer Singapore :2016. - ix, 172 p. :ill., digital ;24 cm. - Springer topics in signal processing,71866-2609 ;. - Springer topics in signal processing ;v.10..

Introduction -- General Concept with Filtering Vectors -- General Concept with Filtering Matrices -- Single-Channel Signal Enhancement in the STFT Domain -- Multichannel Signal Enhancement in the Time Domain -- Multichannel Signal Enhancement in the STFT Domain -- Binaural Signal Enhancement in the Time Domain.

This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.

ISBN: 9789812877390$q(electronic bk.)

Standard No.: 10.1007/978-981-287-739-0doiSubjects--Topical Terms:

533904
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.3822

Signal enhancement with variable span linear filters
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505 0 $a Introduction -- General Concept with Filtering Vectors -- General Concept with Filtering Matrices -- Single-Channel Signal Enhancement in the STFT Domain -- Multichannel Signal Enhancement in the Time Domain -- Multichannel Signal Enhancement in the STFT Domain -- Binaural Signal Enhancement in the Time Domain.
520 $a This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.
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700 1 $a Jensen, Jesper R. $3 2182988
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