Results 221 to 230 of about 424,619 (265)

Unbiased Estimation of the Phase of a Sinusoid

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
Estimation of the phase of a sinusoid is an important problem in signal processing. The usual maximum likelihood estimator is biased and so can produce poor results, especially at low signal-to-noise ratios and/or short data records. It is proven that no unbiased estimator exists; based on the proof, several means of obtaining estimators with less bias
Peters, Keith, Kay, Steven
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Estimation of phase for noisy linear phase signals

IEEE Transactions on Signal Processing, 1996
It is well-known that a discrete-time symmetric signal has a linear-phase Fourier transform. This paper describes a procedure for estimating the parameters associated with a linear-phase signal from noisy measurements. When the data being modeled is composed of a linear-phase signal corrupted by additive Gaussian noise, the approach taken results in ...
Ramakrishna Kakarala, James A. Cadzow
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A phase-coherence detector/Estimator

ICASSP '79. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A phase-coherence estimator formed via overlapped Fast Fourier Transform (FFT) processing and smoothing is presented. It is more efficiently implemented than the more usual magnitude squared coherence (MSC), requiring half the memory. In applications where the phase is the dominant component of the coherence, it provides a reliable estimate of the ...
Roberto Berezdivin, Robert Perl, Robert Braunstein   +2 more
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Phase estimation Under energy conservation

Quantum Information Processing, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sen Han, Xueyuan Hu
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Phase-based estimation of synchrophasors

2016 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), 2016
One of primary grid management challenge is to ensure that these changing power system operating conditions stay within safe limits at all times including potential and probable future contingencies. In this field, one of the most promising enabling technologies is synchrophasor measurements, which require the estimation of the parameters of sinusoids,
Cuccaro, Pasquale, GALLO, Daniele, LANDI, Carmine, LUISO, Mario, ROMANO, Gianmarco   +4 more
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Estimating the phase of synchronized oscillators

Physical Review E, 2008
The state of a collection of phase-locked oscillators is determined by a single phase variable or cyclic coordinate. This paper presents a computational method, Phaser, for estimating the phase of phase-locked oscillators from limited amounts of multivariate data in the presence of noise and measurement errors.
Shai, Revzen, John M, Guckenheimer
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Estimating synchronization signal phase

SPIE Proceedings, 2015
To read a watermark from printed images requires that the watermarking system read correctly after affine distortions. One way to recover from affine distortions is to add a synchronization signal in the Fourier frequency domain and use this synchronization signal to estimate the applied affine distortion.
Robert G. Lyons, John D. Lord
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Phase estimation by message passing

2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577), 2004
The problem of phase estimation in a "turbo receiver" is considered for two different channel models. Several message passing algorithms for phase estimation are derived from the factor graph of the channel models: (1) straight sum-product, applied to a quantized phase model; (2) LMS-type gradient methods; (3) a particle filter.
Justin Dauwels, Hans-Andrea Loeliger
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Frequency Estimation by Phase Unwrapping

IEEE Transactions on Signal Processing, 2010
Single frequency estimation is a long-studied problem with application domains including radar, sonar, telecommunications, astronomy and medicine. One method of estimation, called phase unwrapping, attempts to estimate the frequency by performing linear regression on the phase of the received signal.
Robby G. McKilliam, Barry G. Quinn, I. Vaughan L. Clarkson, William Moran 0001   +3 more
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Agnostic estimation for phase retrieval

J. Mach. Learn. Res., 2020
Summary: The goal of noisy high-dimensional phase retrieval is to estimate an \(s\)-sparse parameter \(\boldsymbol{\beta}^*\in \mathbb{R}^d\) from \(n\) realizations of the model \(Y = (\mathbf{X}^T \boldsymbol{\beta}^*)^2 + \varepsilon \). Based on this model, we propose a significant semi-parametric generalization called misspecified phase retrieval (
Matey Neykov, Zhaoran Wang 0001, Han Liu 0001   +2 more
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