Sparse Representation of Sensor Network Signals Based on the K-SVD Algorithm

IF 0.6 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Z. Zou, Xu He, Yinxia Wang, Jiagao Wu
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引用次数: 0

Abstract

The sparse basis of signals plays a key role in signals processing of wireless sensor networks (WSNs). However, the existing sparse bases, such as principal component analysis (PCA) and discrete cosine transform (DCT), do not support a good recovery effect in WSNs. In this paper, the general K-SVD (K-Means Singular Value Decomposition) is optimized and a new adaptive overcomplete dictionary (K-SVD-DCT) is constructed by extracting features of distributed WSN signals. First of all, we normalize the data and select the DCT matrix as the initial training dictionary D of the K-SVD algorithm, and then use the orthogonal matching pursuit (OMP) method to carry out sparse decomposition on signals, obtaining the sparse representation matrix. Then the dictionary atom is upgraded by iterating D. Eventually, K-SVD-DCT for sensor network signals' sparse representation is obtained after multiple iterations. We evaluate the performances of overcomplete dictionaries constructed by three initial training dictionaries. The experimental results show that the recovery errors of using the K-SVD-DCT are smaller than that of the PCA basis and are similar to that of the DCT basis. However, the successful recovery rate (8.0%) of the DCT basis is much lower than that of the K-SVD-DCT (82%).
基于K-SVD算法的传感器网络信号稀疏表示
信号的稀疏基在无线传感器网络信号处理中起着至关重要的作用。然而,现有的稀疏基,如主成分分析(PCA)和离散余弦变换(DCT),在wsn中并不能支持良好的恢复效果。本文对广义K-SVD (K-Means Singular Value Decomposition)进行了优化,并通过提取分布式WSN信号的特征,构造了一种新的自适应过完备字典(K-SVD- dct)。首先对数据进行归一化处理,选取DCT矩阵作为K-SVD算法的初始训练字典D,然后利用正交匹配追踪(OMP)方法对信号进行稀疏分解,得到稀疏表示矩阵。然后通过迭代d对字典原子进行升级,最终经过多次迭代得到传感器网络信号稀疏表示的K-SVD-DCT。我们评估了由三个初始训练字典构造的过完备字典的性能。实验结果表明,使用K-SVD-DCT的恢复误差小于PCA基,与DCT基相似。然而,DCT基础的成功率(8.0%)远低于K-SVD-DCT的成功率(82%)。
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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来源期刊
Ad Hoc & Sensor Wireless Networks
Ad Hoc & Sensor Wireless Networks 工程技术-电信学
CiteScore
2.00
自引率
44.40%
发文量
0
审稿时长
8 months
期刊介绍: Ad Hoc & Sensor Wireless Networks seeks to provide an opportunity for researchers from computer science, engineering and mathematical backgrounds to disseminate and exchange knowledge in the rapidly emerging field of ad hoc and sensor wireless networks. It will comprehensively cover physical, data-link, network and transport layers, as well as application, security, simulation and power management issues in sensor, local area, satellite, vehicular, personal, and mobile ad hoc networks.
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