An extension of regression-based automatic calibration method for sensor networks

T. Fujino, S. Honda
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引用次数: 1

Abstract

This work proposes a new automatic calibration method for the sensor network which measures the distribution of physical fields. In case of these sensor networks, the regular calibration of the sensors is necessary for obtaining reliable information. However, it is not an easy task in the case of a large scale sensor network, because the manual calibration is time consuming and costly. To solve this problem, this present study proposes a new method which is based on the two concepts of regression analysis and cross validation. In this paper, the new method is explained and the efficient extension is also proposed, and the performance of the proposed methods is verified by a simulation.
基于回归的传感器网络自动标定方法的扩展
本文提出了一种测量物理场分布的传感器网络自动标定方法。在这些传感器网络中,为了获得可靠的信息,需要对传感器进行定期校准。然而,在大规模传感器网络的情况下,这并不是一件容易的事情,因为手动校准既耗时又昂贵。为了解决这一问题,本研究提出了一种基于回归分析和交叉验证两个概念的新方法。本文对新方法进行了说明,提出了有效的扩展,并通过仿真验证了所提方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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