A majorization inequality and its application to distributed Kalman filtering

被引：6
作者：
Del Favero, Simone [1 ]
Zampieri, Sandro [1 ]
机构：
[1] Univ Padua, Dept Informat Eng, I-35131 Padua, Italy
来源：
AUTOMATICA | 2011年 / 47卷 / 11期
关键词：
Majorization inequality; Trace inequality; Expectation of matrix-valued random variables' product; Jump-Markov linear system; Distributed estimation; Kalman filter; Randomized gossip; AVERAGE CONSENSUS;
D O I：
10.1016/j.automatica.2011.08.031
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the analysis of a recently proposed distributed estimation algorithm based on the Kalman filtering and on gossip iterations, we needed to apply a new inequality which is valid for i.id. matrix valued random processes. This inequality can be useful in the analysis of the convergence rate of general jump Markov linear systems. In this paper, we present this inequality. This is based on the theory of majorization and on its use in the analysis of the singular values. Finally we will show the impact of this inequality on the performance analysis of gossip based distributed Kalman filters. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2438 / 2443
页数：6
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