Time-frequency synthesis and filtering

Hlawatsch, F., Matz, G., Boashash, B., Ouelha, S., Stankovic, S. and Hassanpour, H. (2016). Time-frequency synthesis and filtering. In Boualem Boashash (Ed.), Time-frequency signal analysis and processing: a comprehensive reference Second edition ed. (pp. 637-691) Amsterdam, Netherlands: Academic Press. doi:10.1016/B978-0-12-398499-9.00011-X

Author Hlawatsch, F.
Matz, G.
Boashash, B.
Ouelha, S.
Stankovic, S.
Hassanpour, H.
Title of chapter Time-frequency synthesis and filtering
Title of book Time-frequency signal analysis and processing: a comprehensive reference
Place of Publication Amsterdam, Netherlands
Publisher Academic Press
Publication Year 2016
Sub-type Research book chapter (original research)
DOI 10.1016/B978-0-12-398499-9.00011-X
Open Access Status Not yet assessed
Series EURASIP and Academic Press series in signal and image processing
Edition Second edition
ISBN 9780123984999
Editor Boualem Boashash
Chapter number 11
Start page 637
End page 691
Total pages 55
Total chapters 18
Collection year 2017
Language eng
Formatted Abstract/Summary
This chapter presents methods and techniques to design time-varying linear systems such as filters with precise time-frequency (t, f) specifications; this capability can then allow one to model and predict accurately the effects of linear systems on nonstationary signals in applications such as signal cleansing and enhancement. This topic is covered in six sections with appropriate cross-referencing to other chapters. The design of time-varying filters is useful in applications where it is desired to separate, suppress or reduce undesirable nonstationary signal components. This can be done with a number of methods such as the STFT and Gabor transform presented in Section 11.1. In particular, the use of the Gabor expansion for time-varying filtering is illustrated on an application that involves monitoring machine vibrations (Section 11.2). Another illustration of the procedure for designing a time-varying filter is provided in the context of an application involving hands-free telephone speech signals (Section 11.3). Another important application of time-varying filtering, namely signal enhancement, is described using an iterative algorithm based on time-frequency peak filtering (Section 11.4). Then, a method for subspace noise filtering using a time-frequency distribution is described (Section 11.5); and finally a comparison of denoising algorithms for speech enhancement completes the chapter (Section 11.6).
Q-Index Code B1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Book Chapter
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