Signal Enhancement with Variable Span Linear Filters (Springer Topics in Signal Processing, 7) - Hardcover

Book 6 of 16: Springer Topics in Signal Processing

Benesty, Jacob; Christensen, Mads G.; Jensen, Jesper R.

 
9789812877383: Signal Enhancement with Variable Span Linear Filters (Springer Topics in Signal Processing, 7)
Hardcover
ISBN 10: 981287738X ISBN 13: 9789812877383
Publisher: Springer, 2016

Synopsis

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.

"synopsis" may belong to another edition of this title.

From the Back Cover

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.

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2016
Language
English
ISBN 10 
981287738X
ISBN 13 
9789812877383
Binding
Hardcover
Edition number
1
Number of pages
181