Frequency-domain-based least-squares estimation of multifrequency signal parameters

2000 ◽  
Vol 49 (3) ◽  
pp. 555-558 ◽  
Author(s):  
P. Carbone ◽  
E. Nunzi ◽  
D. Petri
Keyword(s):  
Least Squares ◽  
Frequency Domain ◽  
Least Squares Estimation ◽  
Signal Parameters ◽  
Multifrequency Signal

Automated spectral recomposition with application in stratigraphic interpretation

2013 ◽  
Vol 1 (1) ◽  
pp. SA109-SA116 ◽  
Author(s):  
Yihua Cai ◽  
Sergey Fomel ◽  
Hongliu Zeng
Keyword(s):  
Least Squares ◽  
Frequency Domain ◽  
Seismic Response ◽  
Cross Sections ◽  
Reservoir Characterization ◽  
Nonlinear Least Squares ◽  
Significant Frequency ◽  
Signal Parameters ◽  
Frequency Components ◽  
Linear And Nonlinear

Analyzing seismic attributes in the frequency domain is helpful for reservoir characterization. To analyze the reservoir interval of interest in detail, it is important to capture the seismic response at each frequency subset. Spectral recomposition can be used to extract significant components from the seismic spectrum. We propose a separable nonlinear least-squares algorithm for spectral recomposition, which estimates linear and nonlinear parts automatically in separate steps. Our approach is applied to estimate fundamental signal parameters, peak frequencies, and amplitudes, with which the seismic spectrum can be reconstructed. Automated spectral recomposition helps us visualize frequency-dependent geologic features on cross sections and time slices by extracting significant frequency components. Spectral recomposition can also indicate how frequency contents attenuate with time.

The Estimation of Blood Platelet Survival

1972 ◽  
Vol 28 (03) ◽  
pp. 447-456 ◽  
Author(s):  
E. A Murphy ◽  
M. E Francis ◽  
J. F Mustard
Keyword(s):  
Standard Deviation ◽  
Least Squares ◽  
Experimental Error ◽  
Blood Platelet ◽  
Least Squares Estimation ◽  
Systematic Relationship ◽  
Platelet Survival ◽  
The Mean ◽  
Normally Distributed

SummaryThe characteristics of experimental error in measurement of platelet radioactivity have been explored by blind replicate determinations on specimens taken on several days on each of three Walker hounds.Analysis suggests that it is not unreasonable to suppose that error for each sample is normally distributed ; and while there is evidence that the variance is heterogeneous, no systematic relationship has been discovered between the mean and the standard deviation of the determinations on individual samples. Thus, since it would be impracticable for investigators to do replicate determinations as a routine, no improvement over simple unweighted least squares estimation on untransformed data suggests itself.

Least Squares Estimation in Uncertain Differential Equations

2020 ◽  
Vol 28 (10) ◽  
pp. 2651-2655 ◽  
Author(s):  
Yuhong Sheng ◽  
Kai Yao ◽  
Xiaowei Chen
Keyword(s):  
Differential Equations ◽  
Least Squares ◽  
Least Squares Estimation
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