Sample space-time covariance matrix estimation
| Autor: | Stephan Weiss, Connor Delaosa, S. D. Somasundaram, Nicholas J. Goddard, Jennifer Pestana |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Density matrix
Covariance matrix TK 0202 electrical engineering electronic engineering information engineering Sample space Applied mathematics Perturbation (astronomy) Estimator 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Eigenvalues and eigenvectors Mathematics |
| Zdroj: | 2019 International Conference on Acoustics, Speech, and Signal Processing University of Strathclyde ICASSP |
| Popis: | Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations. The variance of the estimation links directly to previously explored perturbation of the analytic eigenvalues and eigenspaces of a parahermitian cross-spectral density matrix when estimated from finite data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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