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Bounding the spectrum of large Hermitian matrices

✍ Scribed by Yunkai Zhou; Ren-Cang Li


Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
398 KB
Volume
435
Category
Article
ISSN
0024-3795

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✦ Synopsis


Estimating upper bounds of the spectrum of large Hermitian matrices has long been a problem with both theoretical and practical significance. Algorithms that can compute tight upper bounds with minimum computational cost will have applications in a variety of areas. We present a practical algorithm that exploits kstep Lanczos iteration with a safeguard step. The k is generally very small, say 5-8, regardless of the large dimension of the matrices. This makes the Lanczos iteration economical. The safeguard step can be realized with marginal cost by utilizing the theoretical bounds developed in this paper. The bounds establish the theoretical validity of a previous bound estimator that has been successfully used in various applications. Moreover, we improve the bound estimator which can now provide tighter upper bounds with negligible additional cost.


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