A comparison of power spectral estimates and applications of the maximum entropy method

1975 ◽  
Vol 80 (4) ◽  
pp. 619-625 ◽  
Author(s):  
Henry R. Radoski ◽  
Paul F. Fougere ◽  
Edward J. Zawalick
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Spectral Estimates ◽  
Power Spectral

Twenty-Four-Hour Power Spectral Analysis by Maximum Entropy Method of Blood Pressure in Primary Hyperaldosteronism

1993 ◽  
Vol 2 (3) ◽  
pp. 189-196 ◽  
Author(s):  
Franco Veglio ◽  
Giuliano Pinna ◽  
Remo Melchio ◽  
Franco Rabbia ◽  
Paola Molino ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Spectral Analysis ◽  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Power Spectral Analysis ◽  
Entropy Method ◽  
Primary Hyperaldosteronism ◽  
Power Spectral

DATA ADAPTIVE SPECTRAL ANALYSIS METHODS

Geophysics ◽  
1971 ◽  
Vol 36 (4) ◽  
pp. 661-675 ◽  
Author(s):  
R. T. Lacoss
Keyword(s):  
Maximum Entropy Method ◽  
Entropy Method ◽  
Likelihood Method ◽  
New Techniques ◽  
Spectral Density Estimation ◽  
New Methods ◽  
Statistical Fluctuations ◽  
Spectral Estimates ◽  
Power Spectral ◽  
Data Adaptive

Two new methods (Maximum Likelihood Method or MLM, and Maximum Entropy Method or MEM) for power spectral density estimation have been experimentally investigated. Both methods, unlike conventional methods, adapt to the actual characteristics of the noise process under study. The new techniques are particularly valuable if the process contains one or more narrow peaks in frequency which are to be resolved. In this case, the output peaks from MEM are proportional to the square of the power in the narrow peaks but the area is equal to power. The peak values of the MLM reflect power directly. Both methods yield the true spectrum if the spectrum changes slowly enough with frequency. Neither of the new methods appears to be unduly sensitive to small statistical fluctuations of the estimated correlation function used to obtain spectral estimates.

scholarly journals CALCULATION OF DIRECTIONAL WAVE SPECTRA BY THE MAXIMUM ENTROPY METHOD OF SPECTRAL ANALYSIS

1984 ◽  
Vol 1 (19) ◽  
pp. 33 ◽  
Author(s):  
MIchael J. Briggs
Keyword(s):  
Spectral Analysis ◽  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Adaptive Method ◽  
Entropy Method ◽  
Wave Spectra ◽  
Spectral Estimates ◽  
Directional Wave ◽  
Data Adaptive ◽  
Using Data

Two analysis techniques for calculating directional wave spectra from measured pressure and biaxial current components were intercompared using data from the 25 October 1980 Atlantic Remote Sensing Land Ocean Experiment (ARSLOE) storm. The two methods are the conventional Fast Fourier Transform (FFT) method and a Maximum Entropy Method (MEM). The MEM is a nonlinear data adaptive method of spectral analysis which is capable of generating higher resolution spectral estimates from shorter data records than conventional FFT methods. The MEM has shown good agreement with the frequency and directional wave spectra calculated using conventional methods.

CROSS‐SPECTRAL ANALYSIS USING MAXIMUM ENTROPY

Geophysics ◽  
1974 ◽  
Vol 39 (3) ◽  
pp. 353-354 ◽  
Author(s):  
Tad Ulrych ◽  
Oliver Jensen
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Power Spectral Analysis ◽  
Entropy Method ◽  
Considerable Success ◽  
Power Spectral ◽  
Bivariate Time Series

A great deal of interest has been shown in the maximum entropy method (MEM) of power spectral analysis originally suggested by Burg (1967, 1968). The application of MEM to problems of geophysical and astronomical interest has met with considerable success (Ulrych, 1972; Ulrych et al., 1973; Smylie et al., 1973; Currie, 1973a, b; and Jensen and Ulrych, 1973). We have recently received a number of enquiries concerning the possibility of computing maximum entropy crosspower spectra. The purpose of this note is to present a method of determining the MEM crosspower spectrum from a knowledge of the MEM autopower spectra of the bivariate time series.

Enhanced Information Recovery in 2D On-and Off-Resonance Nutation NQR using the Maximum Entropy Method

1996 ◽  
Vol 51 (5-6) ◽  
pp. 337-347 ◽  
Author(s):  
Mariusz Maćkowiak ◽  
Piotr Kątowski
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Theoretical Description ◽  
Entropy Method ◽  
Zero Field ◽  
Resonance Effects ◽  
Information Recovery ◽  
Truncation Errors ◽  
Enhanced Resolution ◽  
2D Data

Abstract Two-dimensional zero-field nutation NQR spectroscopy has been used to determine the full quadrupolar tensor of spin - 3/2 nuclei in serveral molecular crystals containing the 3 5 Cl and 7 5 As nuclei. The problems of reconstructing 2D-nutation NQR spectra using conventional methods and the advantages of using implementation of the maximum entropy method (MEM) are analyzed. It is shown that the replacement of conventional Fourier transform by an alternative data processing by MEM in 2D NQR spectroscopy leads to sensitivity improvement, reduction of instrumental artefacts and truncation errors, shortened data acquisition times and suppression of noise, while at the same time increasing the resolution. The effects of off-resonance irradiation in nutation experiments are demonstrated both experimentally and theoretically. It is shown that off-resonance nutation spectroscopy is a useful extension of the conventional on-resonance experiments, thus facilitating the determination of asymmetry parameters in multiple spectrum. The theoretical description of the off-resonance effects in 2D nutation NQR spectroscopy is given, and general exact formulas for the asymmetry parameter are obtained. In off-resonance conditions, the resolution of the nutation NQR spectrum decreases with the spectrometer offset. However, an enhanced resolution can be achieved by using the maximum entropy method in 2D-data reconstruction.

Estimating the distribution of primary reflection coefficients

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1417-1422 ◽  
Author(s):  
Danilo R. Velis
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Reflection Coefficients ◽  
Log Data ◽  
Neuquen Basin ◽  
Neuquén Basin ◽  
Skewness And Kurtosis

The distribution of primary reflection coefficients can be estimated by means of the maximum entropy method, giving rise to smooth nonparametric functions which are consistent with the data. Instead of using classical moments (e.g. skewness and kurtosis) to constraint the maximization, nonconventional sample statistics help to improve the quality of the estimates. Results using real log data from various wells located in the Neuquen Basin (Argentina) show the effectiveness of the method to estimate both robust and consistent distributions that may be used to simulate realistic sequences.

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