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Instantaneous Frequency Estimation Using the ${\rm S}$-Transform
IEEE Signal Processing Letters, 2008Instantaneous frequency (IF) is a fundamental concept that can be found in many disciplines such as communications, speech, and music processing. In this letter, analysis of an IF estimator, based on a time-frequency technique known as S-transform, is performed.
Jin Jiang +2 more
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An adaptive Generalized S-transform for instantaneous frequency estimation
Signal Processing, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin Wang, Xiaofeng Meng 0002
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2-D phase unwrapping and instantaneous frequency estimation
The phase of complex signals is wrapped since it can only be measured modulo-2/spl pi/; unwrapping searches for the 2/spl pi/-combinations that minimize the discontinuity of the unwrapped phase, as only the unwrapped phase can be analyzed and interpreted by further processing.
Spagnolini, Umberto
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Use of the cross Wigner-Ville distribution for estimation of instantaneous frequency [PDF]
This correspondence presents an iterative instantaneous frequency (IF) estimation scheme in which successive IF estimates are obtained from the peak of the cross Wigner-Ville distribution (XWVD) using a reference signal synthesized from an initial IF ...
Boualem Boashash, P O'Shea
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Algorithms for estimating instantaneous frequency
Signal Processing, 2004Three algorithms to estimate instantaneous frequency of a frequency-modulated signal is discussed. These algorithms are based on Hilbert transform, Haar wavelet, and generalized pencil of function (GPOF) methods. While GPOF-based frequency detection method appears to be least sensitive to noise, wavelet-based method is easiest to implement.
Jaideva C. Goswami, Albert E. Hoefel
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Ultra-wideband instantaneous frequency estimation
IEEE Instrumentation & Measurement Magazine, 2015Determining the instantaneous frequency of a signal is required for many applications ranging from radio astronomy to defense applications. Unfortunately, the scan rate is often too long over a wideband spectrum compared to the time scale of signals of interest.
Daniel Lam +4 more
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On the use of the warblet transform for instantaneous frequency estimation
IEEE Transactions on Instrumentation and Measurement, 2004A new digital signal-processing method for instantaneous frequency estimation is here proposed. The attention is mainly paid to signals whose instantaneous frequency trajectories exhibit a periodic evolution versus time. Thanks to an optimized use of the warblet transform, the method assures superior accuracy and resolving capability with respect to ...
Leopoldo Angrisani +3 more
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The statistical performance of some instantaneous frequency estimators
IEEE Transactions on Signal Processing, 1992We examine the class of smoothed central finite differences (SCFD) instantaneous frequency (IF) estimators which are based on finite differencing of the phase of the analytic signal. These estimators are of particular interest since they are closely related to IF estimation via (periodic) first moment , with respect to frequency, of discrete time ...
Brian C. Lovell, Robert C. Williamson
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Bayesian estimation of instantaneous frequency
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96), 2002The problem addressed in this paper is the Bayesian estimation of the instantaneous frequency for parametric nonstationary processes. We carry out Bayesian inference on the unknown parameters using powerful stochastic algorithms, the Markov chain Monte Carlo methods.
A. Doucet, P. Duvaut
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Anisotropic Instantaneous Frequency Estimator
2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2019We present a novel transform, called anisotropic chirplet transform, for the time-frequency analysis of overlapping signals. This transform is motivated by a desire to characterize micro-Doppler signals from the continuous wave radars, especially a challenging topic for instantaneous frequency (IF) estimation in high noise environments.
Yongchun Miao, Haixin Sun, Junfeng Wang
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