A randomised Kaczmarz method-based matrix completion algorithm for data collection in wireless sensor networks

Ying Wang, Guorui Li, Sancheng Peng, Cong Wang, Ying Yuan
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Abstract

The paper proposes a novel matrix completion algorithm for data collection in wireless sensor networks through incorporating a randomised version of Kaczmarz method. By splitting the matrix completion problem into two convex sub-problems and solving the optimal probability computing problem in the randomised Kaczmarz method approximately with the D-optimal design solution, we reduce the reconstruction error and accelerate the convergence speed of the matrix completion computation. The synthetic data experiments show that the proposed algorithm presents more accurate reconstruction accuracy and faster reconstruction speed than the state-of-the-art matrix completion algorithms. Furthermore, we verify the practicality of the proposed matrix completion algorithm in real data collection scenario of wireless sensor networks through the experiments based on the real sensed dataset.
基于随机Kaczmarz方法的无线传感器网络数据采集矩阵补全算法
本文提出了一种基于随机化Kaczmarz方法的无线传感器网络数据采集矩阵补全算法。通过将矩阵补全问题分解为两个凸子问题,用d -最优设计解近似求解随机化Kaczmarz方法中的最优概率计算问题,减小了重构误差,加快了矩阵补全计算的收敛速度。综合数据实验表明,与现有的矩阵补全算法相比,该算法具有更高的重构精度和更快的重构速度。此外,我们还通过基于真实传感数据集的实验验证了所提出的矩阵补全算法在无线传感器网络真实数据采集场景中的实用性。
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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