DocumentCode :
16197
Title :
Hybrid Barankin–Weiss–Weinstein Bounds
Author :
Chengfang Ren ; Galy, Jerome ; Chaumette, Eric ; Larzabal, Pascal ; Renaux, Alexandre
Author_Institution :
LSS, Univ. Paris-Sud, Gif-sur-Yvette, France
Volume :
22
Issue :
11
fYear :
2015
fDate :
Nov. 2015
Firstpage :
2064
Lastpage :
2068
Abstract :
This letter investigates hybrid lower bounds on the mean square error in order to predict the so-called threshold effect. A new family of tighter hybrid large error bounds based on linear transformations (discrete or integral) of a mixture of the McAulay-Seidman bound and the Weiss-Weinstein bound is provided in multivariate parameters case with multiple test points. For use in applications, we give a closed-form expression of the proposed bound for a set of Gaussian observation models with parameterized mean, including tones estimation which exemplifies the threshold prediction capability of the proposed bound.
Keywords :
mean square error methods; prediction theory; Gaussian observation model; McAulay-Seidman bound; hybrid Barankin-Weiss-Weinstein bound; linear transformation; mean square error; Bayes methods; Closed-form solutions; Context; Electronic mail; Estimation; Mean square error methods; Signal to noise ratio; Hybrid bounds; MAPMLE; mean-square-error bounds; parameter estimation; threshold SNR;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2015.2457617
Filename :
7160677
Link To Document :
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