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The corrected least squares (CLS) approach using an over-determined model is investigated to decide the number of sinusoids in additive white noise. Like the total least squares (TLS) approach, the CLS estimation is different from the ordinary least squares (LS) method in that the noise variance is subtracted from the diagonal elements of the correlation matrix of the noisy observed data. Therefore...
Subspace estimation is of importance to high-resolution direction estimation in array processing. In this paper, a new recursive least-squares (RLS) algorithm is proposed for null space estimation, which is used to estimate or track the directions of coherent and/or incoherent signals impinging on a uniform linear array (ULA). Especially by investigating the expectation computation of an inverse matrix,...
High-rate sampled input-output data does not necessarily provide better mean squares error (MSE) for a least squares (LS) estimate of impulse response. The authors propose a scheme to improve the MSE by decimating the high-rate sampled input-output data, calculating the LS estimate of the decimated impulse response, and interpolating the estimate to recover the LS estimate with the original high sampling...
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