SPECTRAL THEORY OF LARGE DIMENSIONAL RANDOM MATRICES AND ITS APPLICATIONS TO WIRELESS COMMUNICATIONS AND FINANCE STATISTICS: RANDOM MATRIX THEORY AND ITS APPLICATIONS

Fang, Zhaoben; Liang, Ying-Chang; Bai, Zhidong

ISBN 10: 981457905X / ISBN 13: 9789814579056

Edité par World Scientific Publishing Company, 2014

A propos de cet article

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Détails bibliographiques

• Titre: SPECTRAL THEORY OF LARGE DIMENSIONAL RANDOM MATRICES AND ITS APPLICATIONS TO WIRELESS COMMUNICATIONS AND FINANCE STATISTICS: RANDOM MATRIX THEORY AND ITS APPLICATIONS
• Éditeur: World Scientific Publishing Company
• Date de parution: 2014
• Langue: anglais
• ISBN à 10 chiffres: 981457905X
• ISBN à 13 chiffres: 9789814579056
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

The book contains three parts: Spectral theory of large dimensional random matrices; Applications to wireless communications; and Applications to finance. In the first part, we introduce some basic theorems of spectral analysis of large dimensional random matrices that are obtained under finite moment conditions, such as the limiting spectral distributions of Wigner matrix and that of large dimensional sample covariance matrix, limits of extreme eigenvalues, and the central limit theorems for linear spectral statistics. In the second part, we introduce some basic examples of applications of random matrix theory to wireless communications and in the third part, we present some examples of Applications to statistical finance.

Présentation de l'éditeur

Practitioners looking for an introduction to the applications of random matrix theory to finance will find this part useful.” Mathematical Reviews Clippings The book contains three parts: Spectral theory of large dimensional random matrices; Applications to wireless communications; and Applications to finance. In the first part, we introduce some basic theorems of spectral analysis of large dimensional random matrices that are obtained under finite moment conditions, such as the limiting spectral distributions of Wigner matrix and that of large dimensional sample covariance matrix, limits of extreme eigenvalues, and the central limit theorems for linear spectral statistics. In the second part, we introduce some basic examples of applications of random matrix theory to wireless communications and in the third part, we present some examples of Applications to statistical finance.