TY - JOUR
N2 - A traditional frequency analysis is not appropriate for observation of properties of non-stationary signals. This stems from the fact that the time resolution is not defined in the Fourier spectrum. Thus, there is a need for methods implementing joint time-frequency analysis (t/f) algorithms. Practical aspects of some representative methods of time-frequency analysis, including Short Time Fourier Transform, Gabor Transform, Wigner-Ville Transform and Cone-Shaped Transform are described in this paper. Unfortunately, there is no correlation between the width of the time-frequency window and its frequency content in the t/f analysis. This property is not valid in the case of a wavelet transform. A wavelet is a wave-like oscillation, which forms its own “wavelet window”. Compression of the wavelet narrows the window, and vice versa. Individual wavelet functions are well localized in time and simultaneously in scale (the equivalent of frequency). The wavelet analysis owes its effectiveness to the pyramid algorithm described by Mallat, which enables fast decomposition of a signal into wavelet components.
L1 - http://www.czasopisma.pan.pl/Content/90293/PDF/Journal10178-VolumeXXI+Issue4_12.pdf
L2 - http://www.czasopisma.pan.pl/Content/90293
PY - 2014
IS - No 4
EP - 741-758
KW - frequency analysis
KW - time-frequency analysis
KW - Short-Time Fourier Transform
KW - Gabor Transform
KW - Wigner-Ville Transform
KW - Cone-Shaped Transform
KW - wavelet analysis
KW - time-scale analysis
KW - wavelet decomposition
KW - filter banks
KW - wavelet packets
A1 - Majkowski, Andrzej
A1 - Kołodziej, Marcin
A1 - Rak, Remigiusz J.
PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation
DA - 2014
T1 - Joint Time-Frequency And Wavelet Analysis - An Introduction
SP - 741-758
UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/90293
DOI - 10.2478/mms-2014-0054
ER -