ﻻ يوجد ملخص باللغة العربية
8000 images of the Solar corona were captured during the June 2001 total Solar eclipse. New software for the alignment of the images and an automated technique for detecting intensity oscillations using multi scale wavelet analysis were developed. Large areas of the images covered by the Moon and the upper corona were scanned for oscillations and the statistical properties of the atmospheric effects were determined. The a Trous wavelet transform was used for noise reduction and Monte Carlo analysis as a significance test of the detections. The effectiveness of those techniques is discussed in detail.
SECIS observations of the June 2001 total solar eclipse were taken using an Fe {sc xiv} 5303 {AA} filter. Automated tools based on wavelet analysis was used to detect intensity oscillations on various areas of the images. Statistical analysis of the
SECIS observations of the June 2001 total solar eclipse were taken using an Fe xiv 5303 A filter. Existing software was modified and new code was developed for the reduction and analysis of these data. The observations, data reduction, study of the a
Bayesian models have become very popular over the last years in several fields such as signal processing, statistics, and machine learning. Bayesian inference requires the approximation of complicated integrals involving posterior distributions. For
We discuss the measurements of the main parameters of the ionospheric response to the total solar eclipse of June 21, 2001. This study is based on using the data from three stations of the global GPS network located in the area of the totality band i
We apply the UV-filtering preconditioner, previously used to improve the Multi-Boson algorithm, to the Polynomial Hybrid Monte Carlo (UV-PHMC) algorithm. The performance test for the algorithm is given for the plaquette gauge action and the $O(a)$-im