Hyperfixation point-source reconstruction by the maximum entropy on the mean method

2002 ◽  
Author(s):  
C. Amblard ◽  
P. Grangeat ◽  
H. Benali ◽  
B. Bendriem
Keyword(s):  
Point Source ◽  
Maximum Entropy ◽  
Source Reconstruction ◽  
The Mean

scholarly journals The Maximum Entropy on the Mean Method for Image Deblurring

2020 ◽  
Author(s):  
Gabriel Rioux ◽  
Rustum Choksi ◽  
Tim Hoheisel ◽  
Pierre Marechal ◽  
Christopher Scarvelis
Keyword(s):  
Maximum Entropy ◽  
Image Deblurring ◽  
The Mean

Distribution of mercury and methylmercury in the sediments of a lowland river system

2005 ◽  
Vol 461 (2057) ◽  
pp. 1335-1355 ◽  
Author(s):  
Jason W Birkett ◽  
John N Lester
Keyword(s):  
Point Source ◽  
Total Mercury ◽  
Sewage Treatment ◽  
River System ◽  
Initial Increase ◽  
Surficial Sediments ◽  
Spatial Trends ◽  
The Mean ◽  
Temporal And Spatial ◽  
Temporal And Spatial Trends

Concentrations of total mercury (T-Hg) and methylmercury (MeHg) were determined in surficial sediments from the River Yare, Norfolk, UK over the period 1986–1998, to assess the temporal and spatial trends of contamination arising from a historical point source discharge. The results demonstrate that the spatial distribution pattern follows that of a distinct pollution plume in the sediments with an initial increase 2–3 km downstream from the point source discharge at Whitlingham sewage treatment works (STW) outfall. Temporally, this pollution plume remains evident, although there has been an overall decline in the mean T-Hg concentrations from 5.4 in 1986 to 1.8 mg kg −1 in 1998. The major factor for this improvement has been the reduction in discharge of metals from the STW, together with burial by a fresh overlay of uncontaminated sediments. MeHg concentrations also exhibited a dispersed pollution plume. Mean concentrations of MeHg fluctuated during the study period between 3.3 and 8.5 μg kg −1 . There has been no concomitant decline in MeHg concentrations over this period. MeHg was found to constitute less than 1% of T-Hg concentrations in the sediments. The weak correlations observed between T-Hg and MeHg concentrations indicate external environmental factors have a significant influence on determining MeHg concentrations in the sedimentary compartment.

Foreground Separation Methods for Satellite and Balloon Experiments

2005 ◽  
Vol 201 ◽  
pp. 71-74
Author(s):  
R. Belén Barreiro ◽  
Michael P. Hobson ◽  
Anthony N. Lasenby ◽  
Patricio Vielva ◽  
Enrique Martínez-González ◽  
...  
Keyword(s):  
Point Source ◽  
Maximum Entropy ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Mexican Hat Wavelet ◽  
Mexican Hat ◽  
Balloon Experiments ◽  
Combined Technique ◽  
Physical Components ◽  
Planck Satellite

A combined technique using the maximum-entropy method (MEM) and the mexican hat wavelet (MHW) to separate and reconstruct the physical components of the microwave sky is presented. We apply this method to simulated observations by the ESA Planck satellite in small patches of the sky. The reconstructed maps of the CMB and foregrounds are improved as compared to those obtained with MEM on its own. Moreover, more accurate point source catalogues are produced at each observing frequency. This technique may also be extended to deal with other multifrequency CMB experiments, including all-sky data.

scholarly journals Effect of Brain-to-Skull Conductivity Ratio on EEG Source Localization Accuracy

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Gang Wang ◽  
Doutian Ren
Keyword(s):  
Source Localization ◽  
Conductivity Ratio ◽  
Source Reconstruction ◽  
Localization Accuracy ◽  
Scalp Eeg ◽  
Skull Conductivity ◽  
Localization Errors ◽  
The Mean ◽  
Eeg Source Localization ◽  
Dipole Sources

The goal of this study was to investigate the influence of the brain-to-skull conductivity ratio (BSCR) on EEG source localization accuracy. In this study, we evaluated four BSCRs: 15, 20, 25, and 80, which were mainly discussed according to the literature. The scalp EEG signals were generated by BSCR-related forward computation for each cortical dipole source. Then, for each scalp EEG measurement, the source reconstruction was performed to identify the estimated dipole sources by the actual BSCR and the misspecified BSCRs. The estimated dipole sources were compared with the simulated dipole sources to evaluate EEG source localization accuracy. In the case of considering noise-free EEG measurements, the mean localization errors were approximately equal to zero when using actual BSCR. The misspecified BSCRs resulted in substantial localization errors which ranged from 2 to 16 mm. When considering noise-contaminated EEG measurements, the mean localization errors ranged from 8 to 18 mm despite the BSCRs used in the inverse calculation. The present results suggest that the localization accuracy is sensitive to the BSCR in EEG source reconstruction, and the source activity can be accurately localized when the actual BSCR and the EEG scalp signals with high signal-to-noise ratio (SNR) are used.

Uncertainty Quantification of Energy Harvesting Systems Using Method of Quadratures and Maximum Entropy Principle

2015 ◽  
Author(s):  
Aditya Nanda ◽  
M. Amin Karami ◽  
Puneet Singla
Keyword(s):  
Energy Harvesting ◽  
Maximum Entropy ◽  
Density Function ◽  
Root Mean Square ◽  
Maximum Entropy Principle ◽  
Mean Square ◽  
Mean Power ◽  
Harvesting Systems ◽  
Entropy Principle ◽  
The Mean

This paper uses the method of Quadratures in conjunction with the Maximum Entropy principle to investigate the effect of parametric uncertainties on the mean power output and root mean square deflection of piezoelectric vibrational energy harvesting systems. Uncertainty in parameters of harvesters could arise from insufficient manufacturing controls or change in material properties over time. We investigate bimorph based harvesters that transduce ambient vibrations to electricity via the piezoelectric effect. Three varieties of energy harvesters — Linear, Nonlinear monostable and Nonlinear bistable are considered in this research. This analysis quantitatively shows the probability density function for the mean power and root mean square deflection as a function of the probability densities of the excitation frequency, excitation amplitude, initial deflection of the bimorph and magnet gap of the energy harvester. The method of Quadratures is used for numerically integrating functions by propagating weighted points from the domain and evaluating the integral as a weighted sum of the function values. In this paper, the method of Quadratures is used for evaluating central moments of the distributions of rms deflection and mean harvested power and, then, in conjunction with the principle of Maximum Entropy (MaxEnt) an optimal density function is obtained which maximizes the entropy and satisfies the moment constraints. The The computed nonlinear density functions are validated against Monte Carlo simulations thereby demonstrating the efficiency of the approach. Further, the Maximum Entropy principle is widely applicable to uncertainty quantification of a wide range of dynamic systems.

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