THE RELATIONSHIP BETWEEN MAXIMUM ENTROPY SPECTRA AND MAXIMUM LIKELIHOOD SPECTRA

Geophysics ◽  
1972 ◽  
Vol 37 (2) ◽  
pp. 375-376 ◽  
Author(s):  
John Parker Burg
Keyword(s):  
Spectral Analysis ◽  
Maximum Likelihood ◽  
Maximum Entropy ◽  
Short Note ◽  
Entropy Method ◽  
Likelihood Method ◽  
Almost All ◽  
The Relationship ◽  
Exact Relationship ◽  
Special Case

In a long needed paper, R. T. Lacoss (1971) has presented many examples of spectra obtained by the maximum likelihood method and by the maximum entropy method and has shown that these newer techniques are in general superior to the more conventional spectral analysis methods. This short note shows that there exists a simple, exact relationship between maximum entropy spectra and maximum likelihood spectra when the correlation function is known at uniform intervals of lag. The data are of this form in almost all practical cases of time series analysis as well as in the special case of wavenumber spectral analysis of wave propagation as seen by a linear array of equally spaced sensors. The wavenumber case will be explicitly considered in this note since it requires the complex variable form of the theory.

Comparison of Methods for Short Crested Wave Analysis

2011 ◽  
Author(s):  
Joris van den Berg
Keyword(s):  
Maximum Likelihood ◽  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Maximum Likelihood Method ◽  
Entropy Method ◽  
Likelihood Method ◽  
Comparison Of Methods ◽  
Wave Analysis ◽  
Small Footprint ◽  
Probe Array

A comparison was made of the robustness and accuracy of Maximum Likelihood Method (MLM) and Maximum Entropy Method (MEM) short crested wave analysis using a small footprint probe array.

Metric for Disassembly and Reuse Decisions: Formulation and Validation

2008 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Deborah Thurston
Keyword(s):  
Maximum Likelihood ◽  
Value Function ◽  
Choice Theory ◽  
Decision Makers ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Maximum Value ◽  
Long Range Planning ◽  
The Relationship ◽  
The Value Function

Design for disassembly and reuse focuses on developing methods to minimize difficulty in disassembly for maintenance or reuse. These methods can gain substantially if the relationship between component attributes (material mix, ease of disassembly etc.) and their likelihood of reuse or disposal is understood. For products already in the marketplace, a feedback approach that evaluates willingness of manufacturers or customers (decision makers) to reuse a component can reveal how attributes of a component affect reuse decisions. This paper introduces some metrics and combines them with ones proposed in literature into a measure that captures the overall value of a decision made by the decision makers. The premise is that the decision makers would choose a decision that has the maximum value. Four decisions are considered regarding a component’s fate after recovery ranging from direct reuse to disposal. A method on the lines of discrete choice theory is utilized that uses maximum likelihood estimates to determine the parameters that define the value function. The maximum likelihood method can take inputs from actual decisions made by the decision makers to assess the value function. This function can be used to determine the likelihood that the component takes a certain path (one of the four decisions), taking as input its attributes, which can facilitate long range planning and also help determine ways reuse decisions can be influenced.

scholarly journals Optical Spectral Analysis of Real-Time TDDFT Using Maximum Entropy Method

2015 ◽  
Vol 14 (3) ◽  
pp. 71-73 ◽  
Author(s):  
Mitsuki TOOGOSHI ◽  
Satoru S. KANO ◽  
Yasunari ZEMPO
Keyword(s):  
Spectral Analysis ◽  
Maximum Entropy ◽  
Real Time ◽  
Maximum Entropy Method ◽  
Entropy Method

Computers and infrared spectroscopy: evolution and revolution

1991 ◽  
Vol 69 (11) ◽  
pp. 1781-1785 ◽  
Author(s):  
D. J. Moffatt ◽  
J. K. Kauppinen ◽  
H. H. Mantsch
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Key Words ◽  
Maximum Entropy ◽  
Input Data ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
History Of ◽  
The Fourier Transform ◽  
The Relationship

A brief history of the relationship between computer and infrared spectroscopist is given with emphasis on the use of the Fourier transform. Subsequently, an algorithm is developed that may be used to devise an objective Fourier self-deconvolution procedure which depends only on the input data and is not subject to the biases that are often introduced in such subjective techniques. Key words: deconvolution, Fourier transform, maximum entropy method.

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
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