基于光滑逼近范数的重构信号算法-lp-NormOptimization.PDF

Advances in Applied Mathematics 应用数学进展, 2014, 3, 140-148 Published Online August 2014 in Hans. /journal/aam /10.12677/aam.2014.33021 A New Method for Signal Reconstruction of l -Norm Optimization p Zhen Zhao, Guoqing Chen Inner Mongolia University, Hohhot Email: 1054488585@ th th th Received: May 24 , 2014; revised: Jun. 20 , 2014; accepted: Jun. 29 , 2014 Copyright © 2014 by authors and Hans Publishers Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). /licenses/by/4.0/ Abstract With the rapid development of information science and technology, the amount of information becomes huge. The demand of technology on information processing will be high and the original traditional information processing methods cannot fully meet the requirements of people. So the study of compression perception theory is very important. The main content of this thesis is the reconstruction algorithm, which has played an important role in the theory of the compressed sensing. In order to overcome the nonsmooth problem in l norm, this paper proposed a new p Maximum Entropy Function Method (MEFM) to solve the lp optimization problem and proved the convergence of the new algorithm. Numerical experiments demonstrated that the new algo- rithm is feasible and effective in signal reconstruction. Keywords Compressed Sensing, Signal Reconstruction, Nonsmooth Optimization, Maximum Entropy Function l 基于光滑逼近 范数的重构信号算法 p 赵 真，陈国庆