[1]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,2014,24(03):198-201.
　LI Yan,WANG Bo.Data Compression and Detection Based on Compressive Sensing[J].,2014,24(03):198-201.
点击复制

基于压缩感知的数据压缩与检测()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年03期
页码:
198-201
栏目:
应用开发研究
出版日期:
2014-03-31

文章信息/Info

Title:
Data Compression and Detection Based on Compressive Sensing
文章编号:
1673-629X（2014）03-0198-04
作者:
李燕; 王博
南京邮电大学 通信与信息工程学院
Author(s):
LI Yan; WANG Bo
关键词:
无线传感网络; 压缩感知; 贝叶斯模型; 信号重构
Keywords:
wireless sensor networks; compressive sensing; Bayesian model; signal reconstruction
分类号:
TN91
文献标志码:
A
摘要:
在无线传感器网络( WSN)中，以往都是采用奈奎斯特技术对信号进行采样并重构，而随着信号频率的增加，应用奈奎斯特技术会使成本大幅度的增加，这是人们所不乐见的。针对这一问题，近年来出现一种新的技术即压缩感知技术，它能利用更少的数据和合适的重构方法得到更精确的原始信号。将稀疏贝叶斯学习( SBL)和压缩感知联合起来，形成了一种在有噪声的情况下更好重建可压缩信号的方法，并进一步将这种方法应用在WSN中，可以在误差允许的范围内有效控制测量数据的维数，在保证一定误差的同时还减少了成本，提高了算法的效率。
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.

相似文献/References:

[1]段军,张清磊.蚁群算法在LEACH路由协议中的应用[J].计算机技术与发展,2014,24(01):65.
　DUAN Jun,ZHANG Qing-lei.Application of Ant Colony Algorithm Based on LEACH Routing Protocol[J].,2014,24(03):65.
[2]吴征 朱军 韩永远.一种新的基于LEACH的WSN分簇协议[J].计算机技术与发展,2010,(05):29.
　WU Zheng,ZHU Jun,HAN Yong-yuan.A New LEACH-Based Clustering Protocol for Wireless Sensor Networks[J].,2010,(03):29.
[3]刘子京 裴文江.基于ZigBee协议的无线传感器网络研究[J].计算机技术与发展,2009,(05):192.
　LIU Zi-jing,PEI Wen-jiang.Research of Wireless Sensor Network Based on ZigBee Protocol[J].,2009,(03):192.
[4]潘伟 黄东.基于Zigbee技术的无线传感网络研究[J].计算机技术与发展,2008,(09):244.
　PAN Wei,HUANG Dong.Research of Wireless Sensor Network Based on Zigbee[J].,2008,(03):244.
[5]张宇晴 郑小建 胡旦华.无线传感网络中基于Agent的高效路由算法的研究[J].计算机技术与发展,2007,(09):120.
　ZHANG Yu-qing,ZHENG Xiao-jian,HU Dan-hua.Agent- Based Efficient Routing Algorithm in Wireless Sensor Networks[J].,2007,(03):120.
[6]张爱华 薄禄裕 盛飞 杨培.基于小波变换的压缩感知在图像加密中的应用[J].计算机技术与发展,2011,(12):145.
　ZHANG Ai-hua,BO Lu-yu,SHENG Fei,et al.Compressed Sensing Based on Single Layer Wavelet Transform for Image Encryption[J].,2011,(03):145.
[7]王韦刚 庄伟胤.基于NIOS Ⅱ的图像压缩感知[J].计算机技术与发展,2012,(04):12.
　WANG Wei-gang,ZHUANG Wei-yin.Compressed Sensing of Image Based on NIOS Ⅱ[J].,2012,(03):12.
[8]王韦刚 胡海峰.基于压缩感知的协作频谱检测[J].计算机技术与发展,2012,(12):241.
　WANG Wei-gang,HU Hai-feng.Collaborative Spectrum Detection Based on Compressed Sensing[J].,2012,(03):241.
[9]张晓咏,熊承义,胡开云,等.基于灰度纹理信息的图像压缩感知编码与重构[J].计算机技术与发展,2013,(01):47.
[10]刘洋,季薇,侯晓赟.一种改进的基于 OMP 重建的宽带频谱感知算法[J].计算机技术与发展,2013,(01):99.
　LIU Yang,JI Wei,HOU Xiao-yun.A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on OMP[J].,2013,(03):99.
[11]李继楼,柯家龙. 基于压缩感知的WSN数据压缩与重构[J].计算机技术与发展,2015,25(09):111.
　LI Ji-lou,KE Jia-long. Data Compression and Recovery of WSN Based on Compressive Sensing[J].,2015,25(03):111.

更新日期/Last Update: 1900-01-01