.png){kind=icon}
返回
Optimal linear estimation for systems with multiple packet dropouts
.png){kind=icon}
PRE
AI
DOI：10.1016/j.automatica.2007.09.023.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with multiple packet dropouts. Based on a packet dropout model, the optimal linear estimators including filter, predictor and smoother are developed via an innovation analysis approach. The estimators are computed recursively in terms of the solution of a Riccati difference equation of dimension equal to the order of the system state plus that of the measurement output. The steady-state estimators are also investigated. A sufficient condition for the convergence of the optimal linear estimators is given. Simulation results show the effectiveness of the proposed optimal linear estimators. (c) 2008 Elsevier Ltd. All rights reserved.
Keyword:
optimal linear estimation
packet dropouts
innovation approach
Riccati difference equation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
机构
引用论文
Testing the equality of several covariance functions for functional data: A supremum-norm based test
PREAI
分享收藏Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏
查看更多内容