Empirical Spectral Distribution of a Matrix Under Perturbation
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DOI: 10.1007/s10959-017-0790-0
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- Romain Allez & Jean-Philippe Bouchaud, 2012. "Eigenvector dynamics: general theory and some applications," Papers 1203.6228, arXiv.org, revised Jul 2012.
- Joel Bun & Romain Allez & Jean-Philippe Bouchaud & Marc Potters, 2015. "Rotational invariant estimator for general noisy matrices," Papers 1502.06736, arXiv.org, revised Oct 2016.
- repec:dau:papers:123456789/10916 is not listed on IDEAS
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Keywords
Random matrices; Perturbation theory; Wigner matrices; Band matrices; Hilbert transform; Spectral density;All these keywords.
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