Distributed Parameter Estimation for Univariate Generalized Gaussian Distribution over Sensor Networks

被引：0
作者：
Chen Liang
Fuxi Wen
Zhongmin Wang
机构：
[1] Xi’an University of Posts and Telecommunications,School of Computer Science and Technology
[2] Singapore University of Technology and Design,Information Systems Technology and Design
来源：
Circuits, Systems, and Signal Processing | 2017年 / 36卷
关键词：
Generalized Gaussian distribution; Shape parameter; Distributed estimation; Sensor networks; Newton–Raphson algorithm;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Generalized Gaussian distribution (GGD) is one of the most prominent and widely used parametric distributions to model the statistical properties of various phenomena. Parameter estimation for these distributions becomes a fundamental problem. However, most of the existing parameter estimation techniques are centralized. In this paper, we consider distributed parameter estimation for univariate GGD over sensor networks. Parameters among different nodes are estimated cooperatively for the proposed diffusion techniques. Numerical studies are carried out to evaluate the efficiency of the proposed methods, in terms of average root mean square error and convergence rate.
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页码：1311 / 1321
页数：10
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