Title :
Noise Parameter Estimation from Quantized Data
Author :
Moschitta, A. ; Carbone, P.
Author_Institution :
Dept. of Electron. & Inf. Eng., Perugia Univ.
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 Cramer-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
Keywords :
AWGN; IEEE standards; maximum likelihood estimation; quantisation (signal); Cramer-Rao lower bound; IEEE 1241; IEEE standard; additive white Gaussian noise; maximum likelihood parametric estimator; noise parameter estimation; quantized data; quantized noisy stimulus; AWGN; Additive white noise; Algorithm design and analysis; Costs; Data engineering; Electronic equipment testing; Gaussian noise; Manufacturing processes; Maximum likelihood estimation; Parameter estimation;
Conference_Titel :
Advanced Methods for Uncertainty Estimation in Measurement, 2006. AMUEM 2006. Proceedings of the 2006 IEEE International Workshop on
Conference_Location :
Sardagna
Print_ISBN :
1-4244-0249-2
DOI :
10.1109/AMYEM.2006.1650750
