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MAD Robust Fusion with Non-Gaussian Channel NoiseIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E92.A, No. 5. (2009), pp. 1293-1300.
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AbstractTo solve the problem of distributed multisensor fusion, the optimal linear methods can be used in Gaussian noise models. In practice, channel noise distributions are usually non-Gaussian, possibly heavy-tailed, making linear methods fail. By combining a classical tool of optimal linear fusion and a robust statistical method, the two-stage MAD robust fusion (MADRF) algorithm is proposed. It effectively performs both in symmetrically and asymmetrically contaminated Gaussian channel noise with contamination parameters varying over a wide range.
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