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Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statistics = random matrix theory and its applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statistics/ Zhidong Bai, Zhaoben Fang, Ying-Chang Liang.
其他題名:	random matrix theory and its applications /
作者:	Bai, Zhidong.
其他作者:	Fang, Zhaoben.
出版者:	[Anhui] :University of Science and Technology of China Press ; : 2014.,
面頁冊數:	1 online resource (xi, 220 p.) :ill. :
附註:	"This work is originally published by University of Science and Technology of China Press in 2010"--Title page verso.
標題:	Matrices. -
電子資源:	http://www.worldscientific.com/worldscibooks/10.1142/9049#t=toc
ISBN:	9789814579063

Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statistics = random matrix theory and its applications /
Bai, Zhidong.

Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statisticsrandom matrix theory and its applications /[electronic resource] :Zhidong Bai, Zhaoben Fang, Ying-Chang Liang. - [Anhui] :University of Science and Technology of China Press ;2014. - 1 online resource (xi, 220 p.) :ill.

"This work is originally published by University of Science and Technology of China Press in 2010"--Title page verso.

Includes bibliographical references (p. 201-215) and index.

Limiting spectral distributions -- Extreme eigenvalues -- Central limit theorems of linear spectral statistics -- Limiting behavior of eigenmatrix of sample covariance matrix -- Wireless communications -- limiting performances of linear and iterative receivers -- Application to finance.

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 ...

ISBN: 9789814579063Subjects--Topical Terms:

528174
Matrices.

LC Class. No.: QA273

Dewey Class. No.: 519.2

Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statistics = random matrix theory and its applications /
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100 1 $a Bai, Zhidong. $3 1061151
245 1 0 $a Spectral theory of large dimensional random matrices and its applications to wireless communications and finance statistics $h [electronic resource] : $b random matrix theory and its applications / $c Zhidong Bai, Zhaoben Fang, Ying-Chang Liang.
260 $a [Anhui] : $a Singapore : $b University of Science and Technology of China Press ; $c 2014. $b World Scientific,
300 $a 1 online resource (xi, 220 p.) : $b ill.
500 $a "This work is originally published by University of Science and Technology of China Press in 2010"--Title page verso.
504 $a Includes bibliographical references (p. 201-215) and index.
505 0 $a Limiting spectral distributions -- Extreme eigenvalues -- Central limit theorems of linear spectral statistics -- Limiting behavior of eigenmatrix of sample covariance matrix -- Wireless communications -- limiting performances of linear and iterative receivers -- Application to finance.
520 $a 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 ...
588 0 $a Print version record.
650 0 $a Matrices. $3 528174
700 1 $a Fang, Zhaoben. $3 1061152
700 1 $a Liang, Ying-Chang. $3 1061153
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/9049#t=toc