当前位置: 首页 > 文章 > 基于压缩感知的农田温度信息处理 安徽农业科学 2015,29 (29) 357-359
Position: Home > Articles > Field Temperature Information Processing Based on Compressed Sensing Journal of Anhui Agricultural Sciences 2015,29 (29) 357-359

基于压缩感知的农田温度信息处理

作  者:
焦俊;王强;范国华;王超;古冉;辜丽川
单  位:
安徽农业大学信息与计算机学院
关键词:
压缩感知;离散余弦变换;正交匹配追踪算法;农田温度
摘  要:
由于农田温度信息在离散余弦基(DCT)下的近似稀疏性,采用压缩感知(CS)技术对每块农田温度信息进行压缩和重构,即将温度信息投影到随机高斯观测矩阵,在接收端通过OMP算法重构出每块农田的温度信息。仿真试验结果表明,在较为稳定的网络环境中,CS算法能够以较少的观测值实现对原始信号的精确重建,降低节点能耗,延长网络生命周期。
译  名:
Field Temperature Information Processing Based on Compressed Sensing
作  者:
JIAO Jun;WANG Qiang;FAN Guo-hua;GU Li-chuan;College of Information and Computer,Anhui Agricultural University;
关键词:
Compressed sensing;;Discrete Cosine Transform(DCT);;Orthogonal Matching Pursuit(OMP);;Farmland temperature
摘  要:
According to the approximately sparsity of field temperature information in Discrete Cosine Transform,Compressed Sensing theory was applied to compress and restructure field temperature information in this paper,that was,field temperature information was projected to arandom Gauss measurement matrix,at the receiving end,each field the temperature data was reconstructed through the OMP algorithm. The simulation result showed that CS algorithm could be used to reduce accurate measurements to reconstruct the original signal groups,save node energy and prolong the network lifetime in the relatively stable environment.

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