Explorations in Time-Frequency Analysis

Understand the methods of modern non-stationary signal processing with authoritative insights from a leader in the field.

List of contents

1. Introduction; Part I. Basics and Constraints: 2. Small data are beautiful; 3. Of signals and noise; 4. On time, frequency, and Gauss; 5. Uncertainty; 6. From time and frequency to time-frequency; 7. Uncertainty revisited; 8. On stationarity; Part II. Geometry and Statistics: 9. Spectrogram geometry 1; 10. Sharpening spectrograms; 11. A digression on Hilbert-Huang transform; 12. Spectrogram geometry 2; 13. The noise case; 14. More on maxima; 15. More on zeros; 16. Back to examples; 17. Conclusion; 18. Annex - software tools.

About the author

Patrick Flandrin holds a Research Director position at the CNRS (Centre National de la Recherche Scientifique), working in the Laboratoire de Physique of the École normale supérieure de Lyon. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and European Association for Signal Processing (EURASIP), and a Member of the French Academy of Sciences.

Summary

An authoritative interpretation of the methods at the heart of modern non-stationary signal processing from a recognised leader in the field. It describes basic concepts and recent advances, explores several example waveform families from bioacoustics, mathematics and physics, and includes numerous illustrative examples.

Product details

• Authors: Patrick Flandrin, Flandrin Patrick
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 30.09.2018
• EAN: 9781108421027
• ISBN: 978-1-108-42102-7
• No. of pages: 226
• Subjects: Natural sciences, medicine, IT, technology > Natural sciences (general); TECHNOLOGY & ENGINEERING / Signals & Signal Processing, Signal Processing, Applied mathematics, Wave mechanics (vibration & acoustics), Communications engineering / telecommunications, Applied physics, Wave mechanics (vibration and acoustics), Digital signal processing (DSP)