计算机技术与发展Issue(3)：198-201,4.DOI:10.3969/j.issn.1673-629X.2014.03.049
基于压缩感知的数据压缩与检测
Data Compression and Detection Based on Compressive Sensing
摘要
Abstract
In wireless sensor networks,signal is sampled and reconstructed using the technology of Nyquist in the past. But it requires a substantial increase in the cost with the growth of the signal frequency,which is that people do not like to see. Recently a new technology is emerged,which is called compressive sensing technology. Compressive sensing can use less data and appropriate reconstruction method to get a more accurate original signal. Put Sparse Bayesian Learning ( SBL) and compressive sensing together to form a better way of re-constructing compressible signal under the noise. This method can effectively control the dimension of measurement data within the range of allowed error in WSN,so you can ensure a certain degree of error while reducing the cost,improving the efficiency of the algorithm.关键词
无线传感网络/压缩感知/贝叶斯模型/信号重构Key words
wireless sensor networks/compressive sensing/Bayesian model/signal reconstruction分类
信息技术与安全科学引用本文复制引用
李燕,王博..基于压缩感知的数据压缩与检测[J].计算机技术与发展,2014,(3):198-201,4.基金项目
国家自然科学基金资助项目(60972041,60972045) （60972041,60972045）
