Inequality-based approximation of matrix eigenvectors
András Kocsor; József Dombi; Imre Bálint
International Journal of Applied Mathematics and Computer Science (2002)
- Volume: 12, Issue: 4, page 533-538
- ISSN: 1641-876X
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topKocsor, András, Dombi, József, and Bálint, Imre. "Inequality-based approximation of matrix eigenvectors." International Journal of Applied Mathematics and Computer Science 12.4 (2002): 533-538. <http://eudml.org/doc/207608>.
@article{Kocsor2002,
abstract = {A novel procedure is given here for constructing non-negative functions with zero-valued global minima coinciding with eigenvectors of a general real matrix A. Some of these functions are distinct because all their local minima are also global, offering a new way of determining eigenpairs by local optimization. Apart from describing the framework of the method, the error bounds given separately for the approximation of eigenvectors and eigenvalues provide a deeper insight into the fundamentally different nature of their approximations.},
author = {Kocsor, András, Dombi, József, Bálint, Imre},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {error bounds; eigenvalues; eigenvectors; inequalities; iterative methods; non-negative functions; global minima; optimization},
language = {eng},
number = {4},
pages = {533-538},
title = {Inequality-based approximation of matrix eigenvectors},
url = {http://eudml.org/doc/207608},
volume = {12},
year = {2002},
}
TY - JOUR
AU - Kocsor, András
AU - Dombi, József
AU - Bálint, Imre
TI - Inequality-based approximation of matrix eigenvectors
JO - International Journal of Applied Mathematics and Computer Science
PY - 2002
VL - 12
IS - 4
SP - 533
EP - 538
AB - A novel procedure is given here for constructing non-negative functions with zero-valued global minima coinciding with eigenvectors of a general real matrix A. Some of these functions are distinct because all their local minima are also global, offering a new way of determining eigenpairs by local optimization. Apart from describing the framework of the method, the error bounds given separately for the approximation of eigenvectors and eigenvalues provide a deeper insight into the fundamentally different nature of their approximations.
LA - eng
KW - error bounds; eigenvalues; eigenvectors; inequalities; iterative methods; non-negative functions; global minima; optimization
UR - http://eudml.org/doc/207608
ER -
References
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