SOME REMARKS ON THE DOZIER–SILVERSTEIN THEOREM FOR RANDOM MATRICES WITH DEPENDENT ENTRIES

DOI10.1142/S2010326312500177zbMath1282.60006MaRDI QIDQ2844433

Radosław Adamczak

Publication date: 28 August 2013

Published in: Random Matrices: Theory and Applications (Search for Journal in Brave)

zbMATH Keywords

random matricesdistribution of eigenvaluescircular lawinformation plus noise matrices

Mathematics Subject Classification ID

Random matrices (probabilistic aspects) (60B20)

Related Items (10)

On the Spectrum of Sample Covariance Matrices for Time Series ⋮ On the convergence of the extremal eigenvalues of empirical covariance matrices with dependence ⋮ Marchenko-Pastur law for a random tensor model ⋮ A short proof of the Marchenko-Pastur theorem ⋮ On Sufficient Conditions in the Marchenko--Pastur Theorem ⋮ Concentration of the empirical spectral distribution of random matrices with dependent entries ⋮ LLN for quadratic forms of long memory time series and its applications in random matrix theory ⋮ Circular law for random matrices with exchangeable entries ⋮ On the universality of spectral limit for random matrices with martingale differences entries ⋮ Circular law for random matrices with unconditional log-concave distribution

Cites Work

• Unnamed Item
• Universality and the circular law for sparse random matrices
• Circular law for noncentral random matrices
• On the Marchenko-Pastur and circular laws for some classes of random matrices with dependent entries
• Circular law, extreme singular values and potential theory
• On limit theorem for the eigenvalues of product of two random matrices
• A generalization of the Lindeberg principle
• Power-law estimates for the central limit theorem for convex sets
• The circular law for random matrices
• Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices
• Spectral analysis of large dimensional random matrices
• Concentration of measure and spectra of random matrices: applications to correlation matrices, elliptical distributions and beyond
• Circular law
• Isoperimetric problems for convex bodies and a localization lemma
• The convergence on spectrum of sample covariance matrices for information-plus-noise type data
• Random matrices: universality of ESDs and the circular law
• On the empirical distribution of eigenvalues of large dimensional information-plus-noise-type matrices
• Circular law theorem for random Markov matrices
• LARGE INFORMATION PLUS NOISE RANDOM MATRIX MODELS AND CONSISTENT SUBSPACE ESTIMATION IN LARGE SENSOR NETWORKS
• NO EIGENVALUES OUTSIDE THE SUPPORT OF THE LIMITING SPECTRAL DISTRIBUTION OF INFORMATION-PLUS-NOISE TYPE MATRICES
• On the limiting empirical measure of eigenvalues of the sum of rank one matrices with log-concave distribution
• A law of large numbers for finite-range dependent random matrices

This page was built for publication: SOME REMARKS ON THE DOZIER–SILVERSTEIN THEOREM FOR RANDOM MATRICES WITH DEPENDENT ENTRIES