Fr. 135.00

Signal Enhancement with Variable Span Linear Filters

English · Paperback / Softback

Shipping usually within 6 to 7 weeks

Description

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This book introduces readers to the novelconcept of variable span speech enhancement filters, and demonstrates how itcan be used for effective noise reduction in various ways. Further, the bookprovides the accompanying Matlab code, allowing readers to easily implement themain ideas discussed. Variable span filters combine the ideas of optimal linearfilters with those of subspace methods, as they involve the jointdiagonalization of the correlation matrices of the desired signal and thenoise. The book shows how some well-known filter designs, e.g. the minimumdistortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (includingtheir new generalizations) can be obtained using the variable span filterframework. It then illustrates how the variable span filters can be applied invarious contexts, namely in single-channel STFT-based enhancement, inmultichannel enhancement in both the time and STFT domains, and, lastly, intime-domain binaural enhancement. In these contexts, the properties of thesefilters are analyzed in terms of their noise reduction capabilities and desiredsignal distortion, and the analyses are validated and further explored insimulations.

List of contents

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.

Summary

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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