Research Article
Research on Compressed Sensing Signal Reconstruction Algorithm Based on Smooth Graduation Norm
@INPROCEEDINGS{10.1007/978-3-319-73317-3_11, author={Xuan Chen}, title={Research on Compressed Sensing Signal Reconstruction Algorithm Based on Smooth Graduation Norm}, proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings}, proceedings_a={ADHIP}, year={2018}, month={2}, keywords={Compressed reconstruction norm Smooth graduation}, doi={10.1007/978-3-319-73317-3_11} }- Xuan Chen
Year: 2018
Research on Compressed Sensing Signal Reconstruction Algorithm Based on Smooth Graduation Norm
ADHIP
Springer
DOI: 10.1007/978-3-319-73317-3_11
Abstract
The compressed signal reconstruction of the sensing node has been a hot research topic for the mobile Internet. At present, some reconstruction algorithms finally adopt the minimum norm optimization algorithm. In order to solve the roughness, poor derivability and other defects of the minimum norm function, this paper constructs the smooth graduation algorithm based on norm, proves the monotonicity of the function and the sequence convergence of the optimal solution, and finally verifies the effectiveness of the function through examples. In the simulation experiment, the signal reconstruction algorithm and the classical OMP algorithm were compared, and the results show that it receives better reconstruction effects, small error and high precision.