The relation between the response spectrum and the phase difference spectrum

1996 ◽  
Vol 9 (3) ◽  
pp. 371-376 ◽  
Author(s):  
Feng-Xin Zhao ◽  
Yu-Xian Hu
Keyword(s):  
Phase Difference ◽  
Response Spectrum ◽  
Difference Spectrum ◽  
Phase Difference Spectrum

scholarly journals Observations of Solar Oscillations in He I 10830 Å

1994 ◽  
Vol 154 ◽  
pp. 65-70 ◽  
Author(s):  
B. Fleck ◽  
F.-L. Deubner ◽  
D. Maier ◽  
W. Schmidt
Keyword(s):  
Wave Spectrum ◽  
Difference Spectrum ◽  
The Other ◽  
Solar Photosphere ◽  
Vacuum Tower ◽  
Cell Interior ◽  
Echelle Spectrograph ◽  
Velocity Signal ◽  
Doppler Shifts ◽  
Phase Difference Spectrum

In continuation of a series of studies devoted to the dynamics of the solar photosphere and chromosphere we have attempted to further extend the range of heights in the atmosphere towards the transition region by including observations of the He I 10830 line. We have recorded simultaneous time series of He I 10830 and Mg I 8807 spectra in the quiet solar atmosphere using the echelle spectrograph at the German Vacuum Tower Telescope in Izaña, Tenerife. The velocity signal derived from the Doppler shifts of He 10830 clearly reveals oscillatory motions. The intensity of He 10830, on the other hand, is hardly affected by the oscillations. In the cell interior the 3-min oscillations prevail. Longer periods are found ain the cell boundaries of the chromospheric network where He absorption is enhanced. The V–V phase difference spectrum between the oscillations of He 10830 and those of Mg 8807 confirms previous observations of a non-propagating component that dominates the acoustic wave spectrum in the chromosphere.

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

What Is The Best Distance And Phase Difference Between The Elements Of Linear Antnna Array

2017 ◽  
pp. 1
Author(s):  
Asma M. N. El Ferjani ◽  
Ahmed S. El Barsha ◽  
AlZaroog Saleh Abdulali
Keyword(s):  
Phase Difference

Characterization of Flood Waves by Rating Curves

1997 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
S.K. Mishra ◽  
M.K. Jain ◽  
S.M. Seth
Keyword(s):  
Phase Difference ◽  
Central India ◽  
Wave Number ◽  
Wave Characteristics ◽  
Travel Wave ◽  
Frame Work ◽  
Rating Curves ◽  
Exact Relationship ◽  
Flood Waves

The flood waves are characterized within the frame-work of loop (or hysteresis) of rating curves. The National Weather Service's Dam Break Flood Forecasting Model is used to generate the flood waves in the downstream valley of the Bargi dam located in Central India. The quantified hystereses, η, of non-dimensional rating curves are related with the corresponding flood wave characteristics, viz., speed of travel, wave number, phase difference, and attenuation. The analysis has led to the development of an exact relationship between η and phase difference. Using the concept of wave zoning, the better performance of the hysteresis based criteria compared with the available criteria is verified using Convex and Muskingum-Cunge routing in the wave zones. η limits are specified for the applicability of these simplified routing models. Furthermore, the envisaged applications of the based analysis are introduced.

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