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The method of perpendiculars of finding estimates from below for minimal singular eigenvalues of random matrices

The method of perpendiculars of finding estimates from below for minimal singular eigenvalues of... AbstractThe lower bounds for the minimal singular eigenvalue of the matrix are obtained under the G-Lindeberg condition and the G-double stochastic condition for the variances of the matrix entries. The new method is based on the G-method of perpendiculars, the REFORM method, the martingale method, and the theory of canonical spectral equations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Random Operators and Stochastic Equations de Gruyter

The method of perpendiculars of finding estimates from below for minimal singular eigenvalues of random matrices

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Publisher
de Gruyter
Copyright
© 2018 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1569-397X
eISSN
1569-397X
DOI
10.1515/rose-2018-0009
Publisher site
See Article on Publisher Site

Abstract

AbstractThe lower bounds for the minimal singular eigenvalue of the matrix are obtained under the G-Lindeberg condition and the G-double stochastic condition for the variances of the matrix entries. The new method is based on the G-method of perpendiculars, the REFORM method, the martingale method, and the theory of canonical spectral equations.

Journal

Random Operators and Stochastic Equations – de Gruyter

Published: Jun 1, 2018

References

  • Sharp lower bounds on the least singular value of a random matrix without the fourth moment condition