Fluctuations for linear spectral statistics of large random covariance matrices. Najim, J. & Yao, J. In *2014 22nd European Signal Processing Conference (EUSIPCO)*, pages 2170-2174, Sep., 2014.

Paper abstract bibtex

Paper abstract bibtex

The theory of large random matrices has proved to be an efficient tool to address many problems in wireless communication and statistical signal processing these last two decades. We provide hereafter a central limit theorem (CLT) for linear spectral statistics of large random covariance matrices, improving Bai and Silverstein's celebrated 2004 result. This fluctuation result should be of interest to study the fluctuations of important estimators in statistical signal processing.

@InProceedings{6952794, author = {J. Najim and J. Yao}, booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)}, title = {Fluctuations for linear spectral statistics of large random covariance matrices}, year = {2014}, pages = {2170-2174}, abstract = {The theory of large random matrices has proved to be an efficient tool to address many problems in wireless communication and statistical signal processing these last two decades. We provide hereafter a central limit theorem (CLT) for linear spectral statistics of large random covariance matrices, improving Bai and Silverstein's celebrated 2004 result. This fluctuation result should be of interest to study the fluctuations of important estimators in statistical signal processing.}, keywords = {covariance matrices;statistical analysis;linear spectral statistics fluctation;large random covariance matrices;wireless communication;statistical signal processing;central limit theorem;CLT;Covariance matrices;Eigenvalues and eigenfunctions;Limiting;Convergence;Random variables;Transforms;Large random matrices fluctuations}, issn = {2076-1465}, month = {Sep.}, url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925019.pdf}, }

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