Title :
The fisher information matrix and the CRLB in a non-AWGN model for the phase retrieval problem
Author_Institution :
Dept. of Math., Univ. of Maryland, College Park, MD, USA
Abstract :
In this paper we derive the Fisher information matrix and the Cramer-Rao lower bound for the non-additive white Gaussian noise model yk = |{x, fk) + μk|2, 1 ≤ k ≤ m, where {f1, · · ·, fm} is a spanning set for Cn and (μ1, ..., μm) are i.i.d. realizations of the Gaussian complex process CN(0, ρ2). We obtain closed form expressions that include quadrature integration of elementary functions.
Keywords :
AWGN; integration; signal reconstruction; signal representation; CRLB; Cramer-Rao lower bound; elementary function quadrature integration; fisher information matrix; nonAWGN model; nonadditive white Gaussian noise model; phase retrieval problem; AWGN; Computational modeling; Mathematical model; Noise measurement; Signal to noise ratio;
Conference_Titel :
Sampling Theory and Applications (SampTA), 2015 International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/SAMPTA.2015.7148875