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- W1839067544 abstract "The problem of maximum-likelihood (ML) completion of a partially specified Toeplitz covariance matrix is crucial in several applications, such as the detection and estimation of more independent Gaussian sources than sensors (m>M) in minimum-redundancy sparse linear antenna arrays. Given the sufficient statistic in the form of the M-variate direct data covariance matrix R/spl circ/, we describe an algorithm that finds a positive-definite completed M/sub /spl alpha//-variate Toeplitz matrix (M/sub /spl alpha///spl Gt/M) with (locally) maximal likelihood ratio (LR). Simulations demonstrate that a statistically high LR is achieved, compared with L/sub 2/ optimisation." @default.
- W1839067544 created "2016-06-24" @default.
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- W1839067544 date "2002-11-13" @default.
- W1839067544 modified "2023-09-23" @default.
- W1839067544 title "Locally optimal maximum-likelihood completion of a partially specified Toeplitz covariance matrix" @default.
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- W1839067544 doi "https://doi.org/10.1109/ssp.2001.955264" @default.
- W1839067544 hasPublicationYear "2002" @default.
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