Sengupta, AM, Mitra, PP (September 1997) Distributions of Singular Values for Some Random Matrices. (Submitted)
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Abstract
The Singular Value Decomposition is a matrix decomposition technique widely used in the analysis of multivariate data, such as complex space-time images obtained in both physical and biological systems. In this paper, we examine the distribution of Singular Values of low rank matrices corrupted by additive noise. Past studies have been limited to uniform uncorrelated noise. Using diagrammatic and saddle point integration techniques, we extend these results to heterogeneous and correlated noise sources. We also provide perturbative estimates of error bars on the reconstructed low rank matrix obtained by truncating a Singular Value Decomposition.
| Item Type: | Paper |
|---|---|
| CSHL Authors: | |
| Communities: | CSHL labs > Mitra lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 25 September 1997 |
| Date Deposited: | 13 Oct 2023 14:45 |
| Last Modified: | 13 Oct 2023 14:45 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/41233 |
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