Results 251 to 260 of about 304,219 (298)

Double Spectral theorem and Two Type Magnitude Coherence Functions

2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005
Studying frequency domain representation for the coherence between two signals is an important basic theoretical problem in the fundamental theories of signal processing. However, magnitude-squared coherence function (MSCFs) could lose some phase information.
Y, Liu, Z, Xie, D M, Xie, X, Zhong, Z, Wang, H, Li   +5 more
openaire   +2 more sources

Analysis of Auditory Evoked Potentials by Magnitude-Squared Coherence

Ear and Hearing, 1989
Evoked potentials are usually analyzed in the time domain (voltage versus time). The most familiar frequency-domain measure, the power spectral density function, displays power as a function of frequency but doesn't distinguish signal power from noise power.
R A, Dobie, M J, Wilson
openaire   +2 more sources

Measures of generalized magnitude-squared coherence: Differences and similarities

Journal of the Franklin Institute, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Malekpour, Sheida, Gubner, John A., Sethares, William A.   +2 more
openaire   +1 more source

Objective detection of 40 Hz auditory evoked potentials: phase coherence vs. magnitude-squared coherence**

Electroencephalography and Clinical Neurophysiology, 1994
The relative performance of phase coherence (PC) and magnitude-squared coherence (MSC) for detection of steady-state evoked potentials was studied using 40 Hz auditory evoked potentials (AEPs) in 10 normal human subjects. In addition, simulation experiments were carried out to determine the effects of signal amplitude and phase variability on detection
R A, Dobie, M J, Wilson
openaire   +2 more sources

Estimation of time-varying magnitude squared coherence functions

Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat. No.97TH8237), 2002
A new method for computing an estimate of the time-varying magnitude squared coherence (MSC) between two data sequences is presented. The method estimates the time-varying MSC function by using a modulator and a lowpass filter and is compared with a method using a bandpass filter and the Hilbert transform through computer simulation.
null Do-Nyeon Kim, null Ill-Whan Cha, null Dae-Hee Youn   +2 more
openaire   +1 more source

Exact Confidence Interval for Magnitude-Squared Coherence Estimates

IEEE Signal Processing Letters, 2004
The magnitude-squared coherence function is widely used in many applications. The approximate confidence interval is only reliable for large data segments. In this letter, an iterative algorithm is provided to compute the exact confidence interval from the cumulative distribution function.
Wang, Shou Yan, Tang, Meng Xing
openaire   +2 more sources

A parametric method for computing magnitude squared coherence

ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
The magnitude squared coherence (MSC) is widely used as a measure of the similarity between a pair of signals. It is normally defined as the squared magnitude of the two signals' cross-spectrum divided by the product of their autospectra. Many methods exist for computing the MSC.
O. Soloman, J. Cadzow, S. Stearns
openaire   +1 more source

Maximum likelihood estimation of magnitude-squared coherence

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988
A maximum-likelihood estimator (MLE) for coherence is derived. The MLE should be unbiased, and there should be no unbiased estimator with smaller variance. An approximation to the MLE, valid for coherence estimates with a large number of degrees of freedom (DOF), is also derived. The two MLE algorithms and two estimators discussed in earlier literature
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Bias of the estimate of magnitude-squared coherence

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1976
A simple accurate approximation for the bias of the estimate of magnitude-squared coherence (MSC) is derived from exact theoretical expressions. Simulation results corroborate the exact and approximate expressions, all of which differ from a previously published simulation result on this topic.
A. Nuttall, G. Carter
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Double Spectral theorem and Two Type Magnitude-Squared Coherence Functions

2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005
Studying frequency domain representation for the coherence between two signals is an important basic theoretical problem in the fundamental theories of signal processing. However, the old magnitude-squared coherence function (OMSCF) has been proved identical to 1, so that to cannot be used to extract any coherence information.
Z X, Xie, H, Li, D M, Xie, Z Y, Li, X F, Zhong, Z F, Wang, Y H, Liu   +6 more
openaire   +2 more sources