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Rank reduction and James-Stein estimation

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2 Author(s)
Manton, J.H. ; Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia ; Hua, Y.

This correspondence addresses the problem of estimating the signal in a signal-plus-Gaussian-noise model when it is known that the signal lies in a given subspace. An alternative to rank reduction is presented. The new estimator has the remarkable property of having a smaller mean-square error than that of the maximum-likelihood (also least-squares) estimator for all parameter values

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Signal Processing, IEEE Transactions on  (Volume:47 ,  Issue: 11 )