Results 241 to 250 of about 191,656 (292)

Anisotropic Instantaneous Frequency Estimator

2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2019
We 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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Algorithms for estimating instantaneous frequency

Signal Processing, 2004
Three 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, 2015
Determining 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, Brandon Buckley, Cejo Lonappan, Asad Madni, Bahram Jalali   +4 more
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Bayesian estimation of instantaneous frequency

Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96), 2002
The 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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Time–frequency distribution spectral polynomials for instantanous frequency estimation

Signal Processing, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Chenshu., Amin, Moeness G.
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Seismic Attenuation Estimation From Instantaneous Frequency

IEEE Geoscience and Remote Sensing Letters, 2010
An approach is proposed for quality (Q) factor estimation from the variation of envelope peak instantaneous frequency (EPIF). For a frequency-independent Q model, assuming that the propagating wavelet can be modeled by a Gaussian function with constant phase, an approximate analytic relation between Q and EPIF variation is derived. Synthetic tests show
Senlin Yang, Jinghuai Gao
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Anelastic Absorption Estimation by Instantaneous Frequency

Proceedings, 2015
The instantaneous frequency is the barycenter of the instantaneous spectrum, and it may provide high-resolution information about the anelastic absorption. This seismic attribute is normally computed by the derivative of the instantaneous phase, but is spiky and unstable when the phase unwrapping process fails.
A.L. Vesnaver, E. Poggiagliolmi
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A Doppler frequency estimate using the instantaneous frequency

Proceedings of 13th International Conference on Digital Signal Processing, 2002
In the preamble it is shown that, under a quasi-stationarity assumption of the multi-component Doppler signal. The assimilation of the Doppler frequency to the mean instantaneous frequency is consistent. Basically, this frequency can be estimated from the first moment of a quadratic time-frequency distribution.
J. Crestel, B. Emile, M. Guitton, D. Menard   +3 more
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Instantaneous Frequency Estimation from Signal Model

2006 International Conference on Emerging Technologies, 2006
Instantaneous frequency is defined as the average of the frequencies present in the signal at a particular instant. To estimate instantaneous frequency, a window of N samples is taken at each time instant. In such techniques, N needs to be large enough.
Khalid Aamir, Mohammad Maud
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A Robust Instantaneous Frequency Estimation Method

Proceedings, 2011
As the instantaneous frequency (IF) estimation using the traditional Hilbert transform (HT) is susceptible to noise, we propose a robust IF estimation method in this paper. The main procedure of the proposed method is applying a geometric series filter to the windowed signal to get the analytic signal. Experimental results on synthetic signals and real
W. Lu, C. K. Zhang
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