Results 231 to 240 of about 4,499,288 (288)

Decimated time-frequency distributions

Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis, 2002
The decimated generalized discrete time-frequency distribution (D-GDTFD) was introduced by O'Hair and Suter (see IEEE International Conference on Circuits and Systems, London, U.K., 30 May-2 June 1994). It trades bandwidth for speed of implementation and requires greatly reduced storage over the generalized discrete time-frequency distribution (GDTFD).
J.R. O'Hair, B.W. Suter
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Robust time-frequency distributions

Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467), 2002
The time-frequency (TF) distributions robust with respect to the heavy-tailed impulse noise are introduced. The robust spectrogram (SPEC) and robust Wigner distribution (WD) are considered. The calculation procedure and properties of these representations are given.
V. Katkovnik, I. Djurovic, L.J. Stankovic   +2 more
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Time-frequency distribution series

Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002
Using the orthogonal-like Gabor (1946) expansion, we decompose the Wigner-Ville (1932, 1948) distribution as a linear combination of localized and oscillated 2D Gaussian functions. Based on the degree of oscillation, we further group those 2D Gaussian functions into time-frequency functions P/sub d/(t,/spl omega/) and thereby obtain the so-called time ...
S. Qian, D. Chen
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Signal synthesis and positive time–frequency distributions

Journal of the Franklin Institute, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shah, Syed Ismail, El-Jaroudi, Amro, Loughlin, Patrick J., Chaparro, Luis F.   +3 more
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Time-Frequency Distribution of Evoked Otoacoustic Emissions

British Journal of Audiology, 1997
Otoacoustic emissions (OAE) are non-stationary signals that vary in time depending on the characteristics of the stimulus. Traditional spectral analysis using Fourier methods ignores the effects of time and can miss important temporal information. Therefore, a better form of spectral analysis requires the use of time-frequency distribution methods ...
Ozdamar, O, Zhang, JW, Kalayci, T, Ulgen, Y   +3 more
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Generalized-marginal time-frequency distributions

Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96), 1996
We introduce a family of time-frequency (TF) distributions with generalized-marginals, i.e., beyond the time-domain and the frequency-domain marginals, in the sense that the projections of a TF distribution along one or more angles are equal to the magnitude squared of the fractional Fourier transforms of the signal.
Xiang-gen Xia, Y. Owechko, B.H. Soffer, R.M. Matic   +3 more
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Positive time-frequency distribution functions

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
We demonstrate the existence of positive joint distributions of time and frequency for arbitrary signals. A method is given to readily generate an infinite number of them for any signal. General properties of these distribution functions are derived and specific examples for some common signals are presented.
L. Cohen, T. Posch
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Zero-tracking time-frequency distributions

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
The zero-tracking time-frequency distribution (TFD) is introduced. The local autocorrelation function of the TFD, defined by an appropriate kernel, is used to form a polynomial whose roots correspond to the instantaneous frequencies of the multicomponent signal. Two techniques for zero-tracking based on the TFD are presented.
null Chenshu Wang, M.G. Amin
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Multiple view time-frequency distributions

Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 2002
We propose a new approach for constructing time-frequency distributions and spectra which achieves improved localisation in the time-frequency plane while retaining the non-negativity property of an energy distribution. The approach is to construct a composite distribution from multiple views of the Wigner-Ville distribution.
G.J. Frazer, B. Boashash
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Multitaper marginal time–frequency distributions

Signal Processing, 2006
Time-frequency distributions (TFDs) belonging to Cohen's class yield a frequency marginal that is equivalent to the periodogram of the signal. It is well-known that the periodogram is not a good spectral estimator since it is not a consistent estimate, i.e. its variance does not decrease with the sample size. Thomson addressed this issue by introducing
Selin Aviyente, William J. Williams
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