Tomographic inversion of measured cross-correlation functions of ocean noise in shallow water using ray theory

2016 ◽  
Vol 62 (4) ◽  
pp. 436-446 ◽  
Author(s):  
V. V. Goncharov ◽  
A. S. Shurup ◽  
O. A. Godin ◽  
N. A. Zabotin ◽  
A. I. Vedenev ◽  
...  
2015 ◽  
Author(s):  
Valeriy V. Goncharov ◽  
Alexandr I. Vedenev ◽  
Alexandr V. Shatravin ◽  
Andrey S. Shurup ◽  
Sergei N. Sergeev ◽  
...  

2019 ◽  
Author(s):  
Carmen Guguta ◽  
Jan M.M. Smits ◽  
Rene de Gelder

A method for the determination of crystal structures from powder diffraction data is presented that circumvents the difficulties associated with separate indexing. For the simultaneous optimization of the parameters that describe a crystal structure a genetic algorithm is used together with a pattern matching technique based on auto and cross correlation functions.<br>


At the beginning of 1969 an elaborate programme of E-layer drift measurements was started at De Bilt. The closely spaced receiver method is being used in combination with an on-line analogue computer which plots the polarity-, auto- and cross-correlation functions of the fading signals. The following results over 1969 and a part of 1970 are presented and discussed: mean hourly values of the N and E components for each month; harmonic analysis and prevailing winds, comparison between results obtained from the intersection of the correlation curves and from the time shifts for maximum cross-correlation; and comparison with the results from other stations at about the same latitude.


1983 ◽  
Vol 78 (6) ◽  
pp. 3981-3989 ◽  
Author(s):  
J. T. Muckerman ◽  
D. W. Noid ◽  
M.S. Child

2003 ◽  
Vol 02 (04) ◽  
pp. 497-505 ◽  
Author(s):  
VLADIMIR A. MANDELSHTAM

Harmonic inversion of Chebyshev correlation and cross-correlation functions by the filter diagonalization method (FDM) is one of the most efficient ways to accurately compute the complex spectra of low dimensional quantum molecular systems. This explains the growing popularity of the FDM in the past several years. Some of its most attractive features are the predictable convergence properties and the lack of adjusting parameters. These issues however are often misunderstood and mystified. We discuss the questions relevant to the optimal choices for the FDM parameters, such as the window size and the number of basis functions. We also demonstrate that the cross-correlation approach (using multiple initial states) is significantly more effective than the conventional autocorrelation approach (single initial state) for the common case of a non-uniform eigenvalue distribution.


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