电子科技大学学报2017，Vol.46Issue(5)：703-708,6.DOI:10.3969/j.issn.1001-0548.2017.05.011
面向压缩感知的基于相关性字典学习算法
Correlation Based Dictionary Learning Algorithm for Compressed Sensing
摘要
Abstract
As a novel technique, compressed sensing, which can reduce energy consumption can promote the development of remote health monitoring systems based on wearable device. Dictionary learning algorithm has attracted much attention because of its improvement of the performance of reconstructing physiological signals in the field of compressed sensing. Usually, conventional dictionary learning algorithms did not consider the implicit correlation inside signals, resulting in that the characteristic of signals cannot be efficiently captured and thus the signal cannot be accurately reconstructed. In this paper, a correlation based dictionary learning algorithm is proposed to apply in compressed sensing, exploit implicit correlation structure inside the physiological signal efficiently, and overcome the shortcoming, poor reconstruction accuracy, of conventional dictionary learning algorithms. Experiments results show that the proposed algorithm can capture the structure of physiological signal adequately, and thus can improve the signal-to-noise ratio for compressed sensing, namely, the compressed physiological signal can be accurately reconstructed.关键词
聚类/压缩感知/字典学习/过完备字典/可穿戴设备Key words
clustering/compressed sensing/dictionary learning/over complete dictionary/wearable device分类
信息技术与安全科学引用本文复制引用
叶娅兰,何文文,程云飞,侯孟书,李云霞..面向压缩感知的基于相关性字典学习算法[J].电子科技大学学报,2017,46(5):703-708,6.基金项目
国家自然科学基金(61501096, 61472067) （61501096, 61472067）
四川省国际科技合作与交流项目(2016HH0020) （2016HH0020）
四川省科技支撑计划(2015GZ0199, 2016FZ0105) （2015GZ0199, 2016FZ0105）
