On: “Maximum‐Entropy Spatial Processing of Array Data,” by R. N. McDonough (GEOPHYSICS, December 1974, p. 843–851)

Geophysics ◽  
1976 ◽  
Vol 41 (1) ◽  
pp. 151-151
Author(s):  
James W. Adams
Keyword(s):  
Time Series ◽  
Maximum Entropy ◽  
Spatial Processing ◽  
Array Data ◽  
Fundamental Error

McDonough has made a fundamental error when he concludes on page 849, “Thus the spectrum (62) can be computed from sufficiently many equally spaced samples of [Formula: see text], sampled in r, by using the above procedure … applicable to time series.”

scholarly journals Comparison of spatial processing techniques for sonar array data

1988 ◽  
Vol 84 (S1) ◽  
pp. S16-S16
Author(s):  
David V. Wyllie ◽  
Brian G. Ferguson ◽  
Garry C. Speechley
Keyword(s):  
Spatial Processing ◽  
Array Data ◽  
Processing Techniques

Separation of Stochastic and Deterministic Information from Seismological Time Series with Nonlinear Dynamics and Maximum Entropy Methods

2007 ◽  
Author(s):  
Rafael M. Gutiérrez ◽  
Gina M. Useche ◽  
Elias Buitrago ◽  
Kevin H. Knuth ◽  
Ariel Caticha ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
Maximum Entropy ◽  
Entropy Methods

Choice of operator length for maximum entropy spectral analysis

Geophysics ◽  
1978 ◽  
Vol 43 (7) ◽  
pp. 1384-1391 ◽  
Author(s):  
James G. Berryman
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Maximum Entropy ◽  
Empirical Evidence ◽  
Discrete Time ◽  
Seismic Data ◽  
A Priori ◽  
Evidence Based ◽  
Maximum Entropy Spectral Analysis ◽  
Discrete Time Series

Empirical evidence based on maximum entropy spectra of real seismic data suggests that M = 2N/ln 2N is a reasonable a priori choice of the operator length M for discrete time series of length N. Various examples support this conclusion.

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