Distributed Parameter Estimation for Univariate Generalized Gaussian Distribution over Sensor Networks

详细信息    查看全文

• 作者：Chen Liang ; Fuxi Wen ; Zhongmin Wang
• 关键词：Generalized Gaussian distribution ; Shape parameter ; Distributed estimation ; Sensor networks ; Newton–Raphson algorithm
• 刊名：Circuits, Systems, and Signal Processing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：36
• 期：3
• 页码：1311-1321
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Electronics and Microelectronics, Instrumentation;
• 出版者：Springer US
• ISSN：1531-5878
• 卷排序：36

文摘

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.