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Time-frequency analysis of postural sway
Journal of Biomechanics, 1995Postural sway during quiet stance has been used to characterize the postural control system. Most studies have used center of pressure (COP) measurements and have assumed stationarity, however, recent research has indicated that COP is not stationary.
T, Schumann +4 more
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Time-Frequency Analysis in the Hearing Process
The Journal of the Acoustical Society of America, 1966The hypothesis that a temporal waveform analysis is performed along the basilar membrane is considered and proved wrong, on the basis of a comparison between the uncertainty principle in Fourier analysis and the time-frequency relations in the cochlea, obtainable from experimental data.
G, Gambardella, G, Trautteur
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2011
Let z be a signal in \(L^2(\mathbb{Z}_{N})\). Then we say that z is time-localized near n0 if all components z(n) are 0 or relatively small except for a few values of n near n0. An orthonormal basis B for \(L^2(\mathbb{Z}_{N})\) is said to be time-localized if every signal in B is time-localized.
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Let z be a signal in \(L^2(\mathbb{Z}_{N})\). Then we say that z is time-localized near n0 if all components z(n) are 0 or relatively small except for a few values of n near n0. An orthonormal basis B for \(L^2(\mathbb{Z}_{N})\) is said to be time-localized if every signal in B is time-localized.
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A Nonlinear Time-Frequency Analysis Method
IEEE Transactions on Signal Processing, 2004An alternative method of time-frequency signal analysis is introduced and is compared with the conventional discrete Fourier transfer (DFT)-based methods. The structure of the proposed algorithm and its mathematical properties are presented. The proposed algorithm has a nonlinear structure that provides a frequency-adaptivity feature.
Masoud Karimi-Ghartemani +1 more
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Analysis in a finite time-frequency plane
IEEE Transactions on Signal Processing, 2000We revise our conjecture concerning signals realizing the lower bound on compaction in the phase plane to include a forgotten case of periodization and indicate that this case can be used to develop an orthonormal basis for data lengths N that are the square of an integer.
Victor E. DeBrunner +2 more
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2017
Signals are in general nonstationary. A complete representation of nonstationary signals requires frequency analysis that is local in time, resulting in the time-frequency analysis of signals. The Fourier transform analysis has long been recognized as the great tool for the study of stationary signals and processes where the properties are ...
Lokenath Debnath, Firdous A. Shah
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Signals are in general nonstationary. A complete representation of nonstationary signals requires frequency analysis that is local in time, resulting in the time-frequency analysis of signals. The Fourier transform analysis has long been recognized as the great tool for the study of stationary signals and processes where the properties are ...
Lokenath Debnath, Firdous A. Shah
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2016
This chapter is a logical continuation of the previous chapter on signal changes. The consideration of nonstationary signals requires an assortment of analysis tools, to highlight different aspects of importance. Many scientific and technical activities are interested on such, for medical purposes, for earthquake study, for machine maintenance, for ...
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This chapter is a logical continuation of the previous chapter on signal changes. The consideration of nonstationary signals requires an assortment of analysis tools, to highlight different aspects of importance. Many scientific and technical activities are interested on such, for medical purposes, for earthquake study, for machine maintenance, for ...
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2017
Fourier-analysis provides a description of a given data set in terms of monochromatic oscillations without any time information. It is thus mostly useful for stationary signals. If the spectrum changes in time it is desirable to obtain information about the time at which certain frequencies appear. This can be achieved by applying Fourier analysis to a
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Fourier-analysis provides a description of a given data set in terms of monochromatic oscillations without any time information. It is thus mostly useful for stationary signals. If the spectrum changes in time it is desirable to obtain information about the time at which certain frequencies appear. This can be achieved by applying Fourier analysis to a
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Time-frequency clustering and discriminant analysis
Statistics & Probability Letters, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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