DocumentCode :
706055
Title :
Signal processing applications of free probability theory
Author :
Ryan, Oyvind ; Debbah, Merouane
Author_Institution :
Dept. of Inf., Univ. of Oslo, Oslo, Norway
fYear :
2007
fDate :
3-7 Sept. 2007
Firstpage :
1181
Lastpage :
1185
Abstract :
Situations in many fields of research, such as digital communications, nuclear physics and mathematical finance, can be modelled with random matrices. When the matrices get large, free probability theory is an invaluable tool for describing the asymptotic behaviour of many systems. It will be shown how free probability can be used to aid in source detection for certain systems. Sample covariance matrices for systems with noise are the starting point in our source detection problem. Multiplicative free deconvolution is shown to be a method which can aid in expressing limit eigenvalue distributions for sample covariance matrices, and to simplify estimators for eigenvalue distributions of covariance matrices.
Keywords :
covariance matrices; eigenvalues and eigenfunctions; probability; signal processing; covariance matrices; deconvolution; digital communications; eigenvalue distributions; free probability theory; mathematical finance; nuclear physics; random matrices; signal processing; source detection problem; Convolution; Covariance matrices; Deconvolution; Eigenvalues and eigenfunctions; Mathematical model; Noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2007 15th European
Conference_Location :
Poznan
Print_ISBN :
978-839-2134-04-6
Type :
conf
Filename :
7098991
Link To Document :
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