منابع مشابه
Note for Cramer-Rao Bounds
• (z)r and (z)i denote the real and imaginary part of z. II. CONSTRAINED CRAMER-RAO BOUND A. Problem Statement Problem statement and notation are based on [1]. • a: a K × 1 non-random vector which are to be estimated. • r: an observation of a random vector . • â (R): an estimate of a basing on the observed vector r . It is required that â (R) satisfies M nonlinear equality constraints (M < K), ...
متن کاملComputing Constrained Cramer Rao Bounds
We revisit the problem of computing submatrices of the Cramér-Rao bound (CRB), which lower bounds the variance of any unbiased estimator of a vector parameter θ. We explore iterative methods that avoid direct inversion of the Fisher information matrix, which can be computationally expensive when the dimension of θ is large. The computation of the bound is related to the quadratic matrix program...
متن کاملCramer-Rao lower bounds for atomic decomposition
In a previous paper [1] we presented a method for atomic decomposition with chirped, Gabor functions based on maximum likelihood estimation. In this paper we present the Cramér-Rao lower bounds for estimating the seven chirp parameters, and the results of a simulation showing that our sub-optimal, but computationally tractable, estimators perform well in comparison to the bound at low signal-to...
متن کاملCramer-Rao bounds for deterministic modal analysis
How accurately can deterministic modes be identified from a finite record of noisy data? In this paper we answer this question by computing the Cramer-Rao bound on the error covariance matrix of any unbiased estimator of mode parameters. The bound is computed for many of the standard parametric descriptions of a mode, including autoregressive and moving average parameters, poles and residues, a...
متن کاملCramer-Rao bounds for blind multichannel estimation
Certain blind channel estimation techniques allow the identification of the channel up to a scale or phase factor. This results in singularity of the Fisher Information Matrix (FIM). The Cramér–Rao Bound, which is the inverse of the FIM, is then not defined. To regularize the estimation problem, one can impose constraints on the parameters. In general, many sets of constraints are possible but ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1987
ISSN: 0090-5364
DOI: 10.1214/aos/1176350602