Spectral convergence for a general class of random matrices
Let be an M×N complex random matrix with i.i.d. entries having mean zero and variance 1/N and consider the class of matrices of the type , where , and are Hermitian nonnegative definite matrices, such that and have bounded spectral norm with being diagonal, and is the nonnegative definite square root of . Under some assumptions on the moments of the entries of , it is proved in this paper that, for any matrix with bounded trace norm and for each complex z outside the positive real line, almost surely as M,N-->[infinity] at the same rate, where [delta]M(z) is deterministic and solely depends on and . The previous result can be particularized to the study of the limiting behavior of the Stieltjes transform as well as the eigenvectors of the random matrix model . The study is motivated by applications in the field of statistical signal processing.
Year of publication: |
2011
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Authors: | Rubio, Francisco ; Mestre, Xavier |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 81.2011, 5, p. 592-602
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Publisher: |
Elsevier |
Keywords: | Random matrix theory Stieltjes transform Multivariate statistics Sample covariance matrix Separable covariance model |
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