Results 131 to 140 of about 2,995,639 (168)
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ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003
The author considers the transformation of bilinear time-frequency distributions for the case of a linear time-variant transformation of the signal. The conditions for the output to be representable, that is, for a signal to exist which gives the output distribution, are derived and related to the general question of time-frequency filtering. >
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The author considers the transformation of bilinear time-frequency distributions for the case of a linear time-variant transformation of the signal. The conditions for the output to be representable, that is, for a signal to exist which gives the output distribution, are derived and related to the general question of time-frequency filtering. >
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Tomography time-frequency transform
IEEE Transactions on Signal Processing, 2002The paper shows that the fractional Fourier transform (FRFT) of a signal is the Radon transform of the time-frequency distribution of the same signal. Therefore, a time-frequency distribution known as the tomography time-frequency transform (TTFT) is defined as the inverse Radon transform of the FRFT of the signal.
Feng Zhang, Guoan Bi, Yan Qiu Chen
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IEEE Transactions on Information Theory, 1964
This paper develops a concept of duality, called time-frequency duality, which is applicable to a class of networks called communication-signal-processing networks. Such networks consist of an interconnection of basic elements such as filters, mixers, delay lines, etc.
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This paper develops a concept of duality, called time-frequency duality, which is applicable to a class of networks called communication-signal-processing networks. Such networks consist of an interconnection of basic elements such as filters, mixers, delay lines, etc.
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The statistics of time–frequency analysis
Journal of the Franklin Institute, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Robust time-frequency distributions
Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467), 2002The 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.
Vladimir Katkovnik +2 more
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IEEE Signal Processing Magazine, 1999
It has been well understood that a given signal can be represented in an infinite number of different ways. Different signal representations can be used for different applications. For example, signals obtained from most engineering applications are usually functions of time. But when studying or designing the system, we often like to study signals and
Shie Qian, Dapang Chen
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It has been well understood that a given signal can be represented in an infinite number of different ways. Different signal representations can be used for different applications. For example, signals obtained from most engineering applications are usually functions of time. But when studying or designing the system, we often like to study signals and
Shie Qian, Dapang Chen
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Time-Frequency Filters and Time-Frequency Expansions
1998The separation of signal components occupying effectively disjoint regions of the TF plane is a fundamental problem of TF signal processing that is encountered in many applications. A related problem is the parsimonious representation (expansion) of signals located in a given TF region. In this chapter, we propose solutions to both problems.
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Quadralinear time-frequency representations
1995 International Conference on Acoustics, Speech, and Signal Processing, 2002In time-frequency analysis there are four bilinear domains commonly used: time-frequency, ambiguity, temporal auto-correlation, and spectral auto-correlation. This paper introduces four new domains that are quadralinear in the signal. These four domains are each a function of three of the four variables used in the bilinear domains. Properties of these
Jeffrey C. O'Neill, William J. Williams
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1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002
A strip filter, which is a time-varying generalization of linear time-invariant filters, selects signals having energy in a strip-shaped region in the time-frequency plane. Its eigenfunctions are a set of chirps oriented parallel to the strip in time-frequency.
Beth A. Weisburn, Ramachandra G. Shenoy
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A strip filter, which is a time-varying generalization of linear time-invariant filters, selects signals having energy in a strip-shaped region in the time-frequency plane. Its eigenfunctions are a set of chirps oriented parallel to the strip in time-frequency.
Beth A. Weisburn, Ramachandra G. Shenoy
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Time--frequency analysis of biosignals
IEEE Engineering in Medicine and Biology Magazine, 2009The wavelet transform has a powerful time-frequency analysis and signal-coding tool suitable for use in the manipulation of complex nonstationary signals. This article provides an overview of the emerging role of wavelet-transform analysis in biomedical signal processing and analysis.
Addison, Paul +2 more
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