In this paper, the parametric estimation of Additive White Gaussian Noise is considered, when available data are obtained from a quantized noisy stimulus. The Cramér-Rao Lower Bound is derived, and the statistically efficiency of a maximum likelihood parametric estimator is discussed, along with the estimation algorithm proposed in IEEE standard IEEE 1241
Noise Parameter Estimation From Quantized Data
MOSCHITTA, Antonio;CARBONE, Paolo
2006
Abstract
In this paper, the parametric estimation of Additive White Gaussian Noise is considered, when available data are obtained from a quantized noisy stimulus. The Cramér-Rao Lower Bound is derived, and the statistically efficiency of a maximum likelihood parametric estimator is discussed, along with the estimation algorithm proposed in IEEE standard IEEE 1241File in questo prodotto:
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