Back to Search
Start Over
Fluctuations of Spiked Random Matrix Models and Failure Diagnosis in Sensor Networks.
- Source :
-
IEEE Transactions on Information Theory . Jan2013, Vol. 59 Issue 1, p509-525. 17p. - Publication Year :
- 2013
-
Abstract
- In this paper, the joint fluctuations of the extreme eigenvalues and eigenvectors of a large dimensional sample covariance matrix are analyzed when the associated population covariance matrix is a finite-rank perturbation of the identity matrix, corresponding to the so-called spiked model in random matrix theory. The asymptotic fluctuations, as the matrix size grows large, are shown to be intimately linked with matrices from the Gaussian unitary ensemble. When the spiked population eigenvalues have unit multiplicity, the fluctuations follow a central limit theorem. This result is used to develop an original framework for the detection and diagnosis of local failures in large sensor networks, for known or unknown failure magnitude. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189448
- Volume :
- 59
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Information Theory
- Publication Type :
- Academic Journal
- Accession number :
- 84489911
- Full Text :
- https://doi.org/10.1109/TIT.2012.2218572