An accelerated iteration algorithm for reconstructing sparse compressed sensing data

2016 ◽  
Author(s):  
Peiyuan Wang ◽  
Jianjun Zhou ◽  
Risheng Wang ◽  
Jie Chen
Keyword(s):  
Compressed Sensing ◽  
Iteration Algorithm ◽  
Sensing Data

scholarly journals Research on Data Fusion Technology Based on Compressed Sensing

2016 ◽  
Vol 12 (08) ◽  
pp. 13 ◽  
Author(s):  
Xianghong Tian
Keyword(s):  
Compressed Sensing ◽  
Data Fusion ◽  
Spatial Correlation ◽  
Traditional Method ◽  
Reconstruction Algorithm ◽  
Fusion Technology ◽  
Fusion Technique ◽  
Sensing Data ◽  
Network Load ◽  
Research Objects

First introduce a traditional compressed sensing data fusion technique, and aiming at the shortcoming of traditional method, a compressed sensing data fusion technology based on temporal-spatial correlation is put forward. Then modeling on the proposed data fusion technique, improve the CS reconstruction algorithm and present the iterative threshold reconstruction algorithm based on temporal-spatial correlation. With the synthetic signals as the research objects, experiments show the effectiveness of the algorithm, further proving that it has obvious improvement for the proposed data fusion technology to reduce the network load and save the network energy.

scholarly journals Compressed Sensing Of Complex Sinusoids Off The Grid

2015 ◽  
Vol 66 (4) ◽  
pp. 238-240 ◽  
Author(s):  
Cheng Ping ◽  
Shi Liu ◽  
Zhao Jiaqun
Keyword(s):  
Compressed Sensing ◽  
Reconstruction Algorithm ◽  
Coordinate Descent ◽  
Linear Estimator ◽  
Iteration Algorithm ◽  
Reconstruction Problem

Abstract To solve off-grid problem in compressed sensing, a new reconstruction algorithm for complex sinusoids is proposed. The compressed sensing reconstruction problem is transformed into a joint optimized problem. Based on coordinate descent approach and linear estimator, a new iteration algorithm is proposed. The results of experiments verify the effectiveness of the proposed method.

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