scholarly journals A statistical analysis of the global distribution of plasmaspheric hiss based on Van Allen Probes wave observations

2017 ◽  
Vol 66 (3) ◽  
pp. 039401
Author(s):  
Xiang Zheng ◽  
Tan Jia-Qiang ◽  
Ni Bin-Bin ◽  
Gu Xu-Dong ◽  
Cao Xing ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Global Distribution ◽  
Van Allen Probes

Global Distribution of Reversed Energy Spectra of Ring Current Protons Based on Van Allen Probes Observations

2021 ◽  
Vol 48 (4) ◽  
Author(s):  
Juan Yi ◽  
Song Fu ◽  
Binbin Ni ◽  
Xudong Gu ◽  
Man Hua ◽  
...  
Keyword(s):  
Ring Current ◽  
Global Distribution ◽  
Energy Spectra ◽  
Van Allen Probes

scholarly journals An empirical model of the global distribution of plasmaspheric hiss based on Van Allen Probes EMFISIS measurements

2020 ◽  
Vol 4 (3) ◽  
pp. 1-20
Author(s):  
JingZhi Wang ◽  
◽  
Qi Zhu ◽  
XuDong Gu ◽  
Song Fu ◽  
...  
Keyword(s):  
Empirical Model ◽  
Global Distribution ◽  
Van Allen Probes

scholarly journals Constructing the global distribution of chorus wave intensity using measurements of electrons by the POES satellites and waves by the Van Allen Probes

2013 ◽  
Vol 40 (17) ◽  
pp. 4526-4532 ◽  
Author(s):  
W. Li ◽  
B. Ni ◽  
R. M. Thorne ◽  
J. Bortnik ◽  
J. C. Green ◽  
...  
Keyword(s):  
Wave Intensity ◽  
Global Distribution ◽  
Van Allen Probes ◽  
Chorus Wave

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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