An estimator of the number of sources based on a sequence of hypothesis test
Estimation of the number of sources embedded in noise is a fundamental problem in statistical signal and array processing. This paper focuses on a non-parametric tool to estimate the number of sources without any information about the signature matrix. We exploit the behavior of eigenvalues of the s...
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Published in | 2011 International Conference on Computational Problem-Solving (ICCP) pp. 1 - 6 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2011
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Subjects | |
Online Access | Get full text |
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Summary: | Estimation of the number of sources embedded in noise is a fundamental problem in statistical signal and array processing. This paper focuses on a non-parametric tool to estimate the number of sources without any information about the signature matrix. We exploit the behavior of eigenvalues of the sample covariance matrix and propose a new estimator based on a sequence of hypothesis test. A series of simulations show its superiority compared to the classical estimators based on information theoretic criteria. |
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ISBN: | 9781457706028 1457706024 |
DOI: | 10.1109/ICCPS.2011.6092299 |