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Eigenvalue algorithm

Known as: Eigensolver, Matrix eigenvalue problem, Symbolic computation of matrix eigenvalues 
In numerical analysis, one of the most important problems is designing efficient and stable algorithms for finding the eigenvalues of a matrix, or… 
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Papers overview

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Highly Cited
2015
Highly Cited
2015
Many quantum algorithms have daunting resource requirements when compared to what is available today. To address this discrepancy… 
Highly Cited
2013
Highly Cited
2013
DMD is a dimensionality reduction technique for time series, with which we can also analyze the dynamic behavior of the time… 
Highly Cited
2012
Highly Cited
2012
The Arnoldi method for standard eigenvalue problems possesses several attractive properties making it robust, reliable and… 
Highly Cited
2009
Highly Cited
2009
In this paper, we describe PEGASUS, an open source Peta Graph Mining library which performs typical graph mining tasks such as… 
Highly Cited
2007
Highly Cited
2007
This book presents the first in-depth, complete, and unified theoretical discussion of the two most important classes of… 
Highly Cited
2004
Highly Cited
2004
We pose and solve the analogue of Slepian's time-frequency concentration problem on the surface of the unit sphere to determine… 
Highly Cited
1994
Highly Cited
1994
An "industrial strength" algorithm for solving sparse symmetric generalized eigenproblems is described. The algorithm has its… 
Highly Cited
1980
Highly Cited
1980
A new algorithm is developed which computes a specified number of eigenvalues in any part of the spectrum of a generalized… 
Highly Cited
1951
Highly Cited
1951
An interpretation of Dr. Cornelius Lanczos' iteration method, which he has named "minimized iterations", is discussed in this…