Asymptotic Cramer-Rao bound for multi-dimensional harmonic models

被引：0
|
作者：
Sajjad, Naheed [1 ]
Boyer, Remy [1 ]
机构：
[1] Univ Paris 11, Lab Signaux & Syst L2S, CNRS, SUPELEC, Paris, France
来源：
2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PTS 1-3, PROCEEDINGS | 2007年
关键词：
parameter estimation; multidimensional signal processing;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The multi-dimensional harmonic model has attracted considerable attention for a variety of applications in signal processing. Stoica and Nehorai have derived the Asymptotic (ie., for large analysis duration) Cramer-Rao lower Bound (ACRB) which represents the minimal theoretical variance in the estimation of the model parameters for a one-dimensional harmonic model of order M. In this work, we generalize and analyze the ACRB associated to a M-order harmonic model of dimension P with P > 1.
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收藏
页码：1041 / +
页数：2
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