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Time-Frequency Analysis for Signal Processing

Wayne King - MathWorks - Watch Now - Duration: 29:49

Time-Frequency Analysis for Signal Processing
Wayne King

Real-world signals often have frequency content that changes over time. Therefore, there is a need to describe signals jointly in time and frequency. Signal processing techniques for time-frequency analysis have been developed in response to this need and constitute a powerful tool for practitioners.

There is no unique or universally optimal time-frequency analysis technique. However, the proliferation of time-frequency analysis techniques should be regarded as an advantage. The signal processing engineer or data scientist is free to choose the method best suited to their type of data or application. In this talk we discuss several time-frequency analysis techniques and illustrate their application to common signal processing workflows. The theoretical underpinnings of these techniques and differences between them are highlighted to elucidate their strengths or weaknesses with respect to specific types of signals and applications. Finally, we discuss the important role that time-frequency analysis plays in AI applications with signals.

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Score: 1 | 2 months ago | 1 reply

Some people asked about some textbook recommendations:
Mallat, S. (2009) "A wavelet tour of signal processing: the sparse way", Academic Press. Chapter 4 is quite good.
Boashash, B. (2016) "Time-Frequency Signal Analysis and Processing: A Comprehensive Reference" Acadmic Press. Very comprehensive.

Hllawatsch, F., Auger, F. (2008) "Time-Frequency Analysis: Concepts and Methods" Wiley. Also, very comprehensive.

Flandrin, P. (2018) "Explorations in Time-Frequency Analysis", Cambridge University Press. This book has some good material on the Hilbert-Huang transform and reassignment.

Score: 0 | 2 months ago | no reply

Thanks for collecting up the resources info.

Score: 1 | 2 months ago | no reply

There was a question in the Q and A asked about Python packages for time-frequency analysis.
LTFAT: this is a partial python port of the free MATLAB toolbox LTFAT. https://pypi.org/project/ltfatpy/

ssqueezepy: an excellent python package for wavelet synchrosqueezing
Librosa: designed for audio processing but has time-frequency capability
Torrence & Compo have a package for continuous wavelet analysis that is open source:
There are Python and MATLAB implementations.
Finally, outside of Python, LTFAT (the Large Time-Frequency Analysis Toolbox) is open source MATLAB, you need base MATLAB to run it but not any toolboxes: