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2008

Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise

9 years 2 months ago
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise
Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing the BLUE usually requires the prior knowledge of the noise covariance matrix and the subspace to which the true signal belongs. However, such prior knowledge is often unavailable in reality, which prevents us from applying the BLUE to real-world problems. To cope with this problem, we give a practical procedure for approximating the BLUE without such prior knowledge. Our additional assumption is that the true signal follows a non-Gaussian distribution while the noise is Gaussian. Keywords signal denoising, best linear unbiased estimator (BLUE), non-Gaussian component analysis (NGCA), Gaussian noise.
Masashi Sugiyama, Motoaki Kawanabe, Gilles Blancha
Added 11 Dec 2010
Updated 11 Dec 2010
Type Journal
Year 2008
Where IEICET
Authors Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Klaus-Robert Müller
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