The least singular value of a random square matrix is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:mi mathvariant="normal">O</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:msup><mml:mi>n</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy="false">/</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math>

Type: Article

Publication Date: 2008-08-01

Citations: 43

DOI: https://doi.org/10.1016/j.crma.2008.07.009

Abstract

Let A be a matrix whose entries are real i.i.d. centered random variables with unit variance and suitable moment assumptions. Then the smallest singular value sn(A) is of order n−1/2 with high probability. The lower estimate of this type was proved recently by the authors; in this Note we establish the matching upper estimate. To cite this article: M. Rudelson, R. Vershynin, C. R. Acad. Sci. Paris, Ser. I 346 (2008). Soit A une matrice dont les entrées sont des variables aléatoires centrées réelles i.i.d. de variance 1 vérifiant une hypothèse adéquate de moment. Alors la plus petite valeur singulière sn(A) est de l'ordre de n−1/2 avec grande probabilité. La minoration de sn(A) a été récemment obtenue par les auteurs ; dans cette Note, nous prouvons la majoration. Pour citer cet article : M. Rudelson, R. Vershynin, C. R. Acad. Sci. Paris, Ser. I 346 (2008).

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