Proposition of a Bayesian model for the propagation of the information in a wireless sensor network

机译：贝叶斯模型在无线传感器网络中传播信息的建议

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摘要

Wireless sensor networks (WSN) are specially distributed sensors deployed for the purpose of sensing and monitoring physical or environmental conditions. Sensor measurements in WSN usually suffer from both random errors (noise) and systematic errors (bias). This poses a major problem in the end application, as the data from the network become progressively uninformative.

机译：无线传感器网络（WSN）是专门分布的传感器，用于感测和监视物理或环境状况。 WSN中的传感器测量通常会遭受随机误差（噪声）和系统误差（偏置）的影响。由于来自网络的数据逐渐变得无用，这在最终应用中造成了一个主要问题。

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《IEEE/ACS International Conference on Computer Systems and Applications》|2015年|1-8|共8页
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Frederic Lehmann; Dina Chaal; Abdelouahid Lyhyaoui;
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关键词
Bayesians models; Data fusion; detection; learning methods; nonlinear signal processing;

机译：贝叶斯模型;数据融合;检测;学习方法;非线性信号处理;

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4. Proposition of a Bayesian model for the propagation of the information in a wireless sensor network [C] . Frederic Lehmann, Dina Chaal, Abdelouahid Lyhyaoui IEEE/ACS International Conference on Computer Systems and Applications . 2015

机译：贝叶斯模型的命题在无线传感器网络中传播信息的传播
5. Development of radio propagation models for wireless sensor networks used in corn fields. [D] . Li, Haixia. 2013

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6. Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks [O] . Tian Wang, Qun Wu, Sheng Wen, 2017

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Proposition of a Bayesian model for the propagation of the information in a wireless sensor network

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