传感器网络中分布式相关温度数据的压缩

Feng Chen, M. Rutkowski, Christopher Fenner, R. Huck, Shuang Wang, Samuel Cheng
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引用次数: 7

摘要

只提供摘要形式。分布式源编码(DSC)正在迅速普及,并有许多很好的应用。然而,有时忽略了一些重要的相关性,例如时间相关性。在本文中,我们考虑了源数据在空间和时间域上的相关性来进行DSC解码。这等同于在我们的算法中积分一个卡尔曼滤波器。在实际的温度网络上进行了测试,结果表明该算法比无时间相关的算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compression of Distributed Correlated Temperature Data in Sensor Networks
Summary form only given. Distributed Source Coding (DSC) is rapidly gaining popularity, and has many good applications. However, some important correlations are sometimes omitted, such as temporal correlation. In this paper, we consider the correlations of the source data both in spatial and temporal domains for DSC decoding. And this is equally to integrate a Kalman filter in our algorithm. We tested our algorithm on the practical temperature network, and the results turn out it achieved better performance than the algorithm without temporal correlation.
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