no. 4
Functional Analysis/Probability Theory
Lower estimates for the singular values of random matrices
[Minorations des valeurs singulières de matrices aléatoires]

Présenté par : Gilles Pisier

Rudelson, Mark1
1 Department of Mathematics, University of Missouri, Columbia, MO 65211, USA
Comptes Rendus. Mathématique, Tome 342 (2006) no. 4, pp. 247-252.

Soit Γ une matrice n×n, ayant pour coefficients des variables aléatoires indépendantes et identiquement distribuées (i.i.d.) vérifiant une décroissance sous-gaussienne des queues. Dans ce travail, nous obtenons des minorations de type polynomial des valeurs singulières de Γ, valables avec une probabilité proche de 1. Nous montrons aussi que si A est une matrice N×n avec N>n, dont les coefficients sont des variables aléatoires sous-gaussiennes i.i.d., alors l'espace E=ARn vérifie avec une grande probablilité les conditions du théorème de Kashin, c'est à dire les normes ℓ2N et ℓ1N sont équivalentes sur E. De plus la distance entre ces normes dépend polynomialement de δ=(N−n)/n.

Let Γ be an n×n matrix, whose entries are independent identically distributed (i.i.d.) random variables satisfying the subgaussian tail estimate. We obtain polynomial type lower estimates of the singular numbers of Γ, which hold with probability close to 1. We also show that if A is an N×n matrix with N>n, whose entries are i.i.d. subgaussian random variables, then with high probability the space E=ARn satisfies the conditions of Kashin's theorem, i.e. the ℓ2N and ℓ1N norms are equivalent on E. Moreover the distance between these norms polynomially depends on δ=(N−n)/n.

Reçu le :
Accepté le :
Publié le :
DOI : 10.1016/j.crma.2005.11.013
Rudelson, Mark 1

1 Department of Mathematics, University of Missouri, Columbia, MO 65211, USA 
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Rudelson, Mark. Lower estimates for the singular values of random matrices. Comptes Rendus. Mathématique, Tome 342 (2006) no. 4, pp. 247-252. doi : 10.1016/j.crma.2005.11.013. http://www.numdam.org/articles/10.1016/j.crma.2005.11.013/

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