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Noise Parameter Estimation From Quantized Data

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2 Author(s)
Moschitta, A. ; Dept. of Electron. & Inf. Eng, Perugia Univ. ; Carbone, P.

In this paper, the parametric estimation of the variance of white Gaussian noise is considered when available data are obtained from a quantized noisy stimulus. The Crameacuter-Rao lower bound is derived, and the statistical efficiency of a maximum-likelihood parametric estimator is discussed, along with the estimation algorithm proposed in IEEE Standard 1241

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Instrumentation and Measurement, IEEE Transactions on  (Volume:56 ,  Issue: 3 )