Signals consisting of multiple frequencies and changing their amplitude while propagating in time generate in many experiments. The analysis of such signals requires special methodological approach and mathematical apparatus, which allows ascertain the main features of the signal by a signal transformation. The general method is to apply Fourier transform analysis. However, Fourier transform analysis provides actual spectra for stationary signals alone. For signals changing their characteristics over time the method of analysis that presents the signal changes in both time and frequency is required, and one of the most valid methods is wavelet transform. The present work is aimed to show the advantages of wavelet transform in comparison with FT, when signals changing their characteristics over time is necessary to investigate.
Pukhova, V. M., Kustov, T. V., Ferrini, G., Time-frequency analysis of non-stationary signals, Contributed paper, in Proceedings of the 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2018, (Saint Petersburg Electrotechnical University "LETI", rus, 29-January 01-February 2018), Institute of Electrical and Electronics Engineers Inc., Saint Petersburg 2018:2018- 1141-1145. 10.1109/EIConRus.2018.8317292 [http://hdl.handle.net/10807/132128]
Time-frequency analysis of non-stationary signals
Ferrini, GabrieleUltimo
2018
Abstract
Signals consisting of multiple frequencies and changing their amplitude while propagating in time generate in many experiments. The analysis of such signals requires special methodological approach and mathematical apparatus, which allows ascertain the main features of the signal by a signal transformation. The general method is to apply Fourier transform analysis. However, Fourier transform analysis provides actual spectra for stationary signals alone. For signals changing their characteristics over time the method of analysis that presents the signal changes in both time and frequency is required, and one of the most valid methods is wavelet transform. The present work is aimed to show the advantages of wavelet transform in comparison with FT, when signals changing their characteristics over time is necessary to investigate.
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