Results 221 to 230 of about 105,341 (258)

Causal Signals—Analytic Signals

2016
It was shown in Chap. 8 that the impulse response of a physical system is zero for negative time. This follows from the principle of causality; the output of the filter cannot precede the signal that created it, in this case, the Dirac distribution which is zero for negative time. The effect cannot precede the cause.
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A NOTE ON ANALYTIC SIGNALS WITH NONLINEAR PHASE

International Journal of Wavelets, Multiresolution and Information Processing, 2009
Instantaneous frequency, defined as the derivative of the phase of a complex analytic representation of the signal, is a basic concept and plays an important role in communication and information processing. It is not unusual to expect that the instantaneous frequency of an analytic signal is nonnegative.
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Micro Signal Extraction and Analytics

2017
This dissertation studies the extraction of signals that have smaller magnitudes—typically one order of magnitude or more—than the dominating signals, or the extraction of signals that have a smaller topological scale than what conventional algorithms resolve. We name such a problem the micro signal extraction problem.
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ϕ-linear canonical analytic signals

Signal Processing, 2018
Abstract In this paper, a ϕ-linear canonical Hilbert transform (ϕ-LCHT) is proposed by a linear combination of a given signal and its parameter Hilbert transform (PHT). Herein, a PHT is a generalized HT based on the linear canonical transform (LCT). Some essential properties of a ϕ-LCHT are also derived.
Yan-Na Zhang 0001, Bing-Zhao Li 0001
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Analytic Properties of Downsampling for Bandlimited Signals

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
In this paper we study downsampling for bandlimited signals. Downsampling in the discrete-time domain corresponds to a removal of samples. For any downsampled signal that was created from a bandlimited signal with finite energy, we can always compute a bandlimited continuous-time signal such that the samples of this signal, taken at Nyquist rate, are ...
Holger Boche, Ullrich J. Mönich
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On analytic signals with nonnegative instantaneous frequencies

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
In this paper, we characterize all analytic signals with band-limited amplitudes and polynomial phases. We show that a signal with band-limited amplitude and polynomial phase is analytic if and only if it has nonnegative constant instantaneous frequency, i.e., the derivative of the phase is a nonnegative constant, and the constant is greater than or ...
Xiang-Gen Xia 0001, Leon Cohen
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Analytical signal processing for pattern recognition

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
The development of a novel technique for the alignment of signals distorted by linear or nonlinear perturbation of the sampling instants is described. This technique considers the analytic signals of the given signals and uses the fact that, if a signal is distorted by a linear time-scale distortion, the contour of the analytic signal in the complex ...
A. Maheswaran, Bruce R. Davis
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Analytical Complexity and Signal Coding

Russian Journal of Mathematical Physics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The Analytic Representation of Band-Pass Signals

Journal of the Franklin Institute, 1980
Abstract The analytic representation of band-pass signals, which is extremely useful in information transmission and radar, is usually obtained by first introducing the Hilbert transform of a signal. We consider this procedure artificial, and propose here to follow the opposite path, which leads, in a natural way, to a motivated definition of the ...
Gonzalez-Velasco, Enrique A., Sanvicente, Emilio   +1 more
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An analytical model for regular respiratory signal

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
In disaster rescue, breathing motion detection is an important approach to searching survivors trapped under debris. Detection of breathing motion is realized by detecting the respiratory signal acquired by the sensing system. In this paper, modeling the regular respiratory signal is studied.
Xin Li, Dengyu Qiao, Ye Li
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