.png){kind=icon}
返回
Continuous Estimation Using Context-Dependent Discrete Measurements
.png){kind=icon}
OA
AI
DOI：10.1109/TAC.2018.2797839.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper considers the problem of continuous state estimation from discrete context-based measurements. Context measurements provide binary information as obtained from the system's environment, e.g., a medical alarm indicating that a vital sign is above a certain threshold. Since they provide state information, these measurements can be used for estimation purposes, similar to standard continuous measurements, especially when standard sensors are biased or attacked. Context measurements are assumed to have a known probability of occurring given the state; in particular, we focus on the probit function to model threshold-based measurements, such as the medical-alarm scenario. We develop a recursive context-aware filter by approximating the posterior distribution with a Gaussian distribution with the same first two moments as the true posterior. We show that the filter's expected uncertainty is boundedwhen the probability of receiving context measurements is lower bounded by some positive number for all system states. Furthermore, we provide an observability-like result-all eigenvalues of the filter's covariance matrix converge to 0 after repeated updates if and only if a persistence of excitation condition holds for the context measurements. Finally, in addition to simulation evaluations, we applied the filter to the problem of estimating a patient's blood oxygen content during surgery using real-patient data.
Keyword:
Context-aware state estimation
discrete context measurements
estimation of blood oxygen content
probit measurement model
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:
7
论文数:
1.3W
被引数:
6.7W
机构
引用论文
Stability Analysis of Networked Control Systems Using a Switched Linear Systems Approach基于切换线性系统方法的网络控制系统稳定性分析
OAAI
OAAI分享收藏State estimation for linear discrete-time systems using quantized measurements使用量化测量的线性离散时间系统的状态估计.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏分享收藏Relating spatial and temporal variability in sediment chlorophylla and carbohydrate distribution with erodibility of a tidal flatEstuaries
EstuariesIF0
PREAI
分享收藏Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and EvolutionPLoS ONEOAAI
PLoS ONEIF0
OAAI分享收藏
查看更多内容