Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

11

CORR
2007
Springer

favoriteEmaildiscussreport

110views Education» more CORR 2007»

Free deconvolution for signal processing applications

13 years 4 months ago

Free deconvolution for signal processing applications

Download folk.uio.no

—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 explained how free probability can be used to estimate covariance matrices. 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.

Øyvind Ryan, Mérouane Debbah

Real-time Traffic

CORR 2007 | Covariance Matrices | Education | Eigenvalue Distributions | Free Probability |

claim paper

Related Content

» Deconvolutive Clustering of Markov States

» A Parallel Algorithm for the Solution of the Deconvolution Problem on Heterogeneous Networ...

» Random Vandermonde MatricesPart II Applications

» Revisiting adaptive leastsquares estimation and application to online sparse signal recove...

» An iterative leastsquares technique for dereverberation

» Hibernets energyefficient sensor networks using analog signal processing

» Sparse coding and dictionary learning based on the MDL principle

» A methodology based on Transportation problem modeling for designing parallel interleaver ...

» Matrixvalued radial basis functions stability estimates and applications

Post Info
More Details (n/a)

Added	13 Dec 2010
Updated	13 Dec 2010
Type	Journal
Year	2007
Where	CORR
Authors	Øyvind Ryan, Mérouane Debbah

Comments (0)