On fast computation of superdiagonal Padé fractions

1982 ◽  
pp. 39-42 ◽  
Author(s):  
William B. Gragg ◽  
Fred G. Gustavson ◽  
Daniel D. Warner ◽  
David Y. Y. Yun
Keyword(s):  
Fast Computation

Fast Computation of Electrical Property of Microstrip Array with AIM

2011 ◽  
Vol 30 (1) ◽  
pp. 238-240
Author(s):  
Xiu-lian He ◽  
Wen-jun Gao ◽  
Yi-cai Ji ◽  
Hong Lei ◽  
Shu-xi Gong
Keyword(s):  
Electrical Property ◽  
Fast Computation ◽  
Microstrip Array

Easy programming for fast computation of S-matrix sensitivities

1988 ◽  
Vol 24 (12) ◽  
pp. 764
Author(s):  
J.-S. Hong
Keyword(s):  
Fast Computation ◽  
S Matrix

scholarly journals Fast computation and practical use of amplitudes at non-Fourier frequencies

2021 ◽  
Author(s):  
Erhard Reschenhofer ◽  
Manveer K. Mangat
Keyword(s):  
High Frequency ◽  
Superior Performance ◽  
High Frequency Data ◽  
Mean Square ◽  
Fast Computation ◽  
Efficient Computation ◽  
Frequency Data ◽  
Second Stage ◽  
Orthogonality Conditions ◽  
Memory Parameter

AbstractIn this paper, it is shown that the performance of various frequency-domain estimators of the memory parameter can be boosted by the inclusion of non-Fourier frequencies in addition to the regular Fourier frequencies. A fast two-stage algorithm for the efficient computation of the amplitudes at these additional frequencies is presented. In the first stage, the naïve sine and cosine transforms are computed with a modified version of the Fast Fourier Transform. In the second stage, these transforms are amended by taking the violation of the standard orthogonality conditions into account. A considerable number of auxiliary quantities, which are required in the second stage, do not depend on the data and therefore only need to be computed once. The superior performance (in terms of root-mean-square error) of the estimators based also on non-Fourier frequencies is demonstrated by extensive simulations. Finally, the empirical results obtained by applying these estimators to financial high-frequency data show that significant long-range dependence is present only in the absolute intraday returns but not in the signed intraday returns.

scholarly journals Fast Computation of Explanations for Inconsistency in Large-Scale Knowledge Graphs

2020 ◽  
Author(s):  
Trung-Kien Tran ◽  
Mohamed H. Gad-Elrab ◽  
Daria Stepanova ◽  
Evgeny Kharlamov ◽  
Jannik Strötgen
Keyword(s):  
Large Scale ◽  
Fast Computation ◽  
Knowledge Graphs
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