CAJ | 학술논문

压缩感知理论是利用信号的稀疏性，采用重构算法通过少量的观测值就可以实现对该信号的精确重构。SL0（Smoothed l0）算法是基于l0范数的稀疏信号重构算法，通过控制参数逐步逼近最优解。针对平滑函数的选取问题，文章提出一种新的平滑函数序列近似l0范数，实现稀疏信号的精确重构。仿真结果表明，在相同实验条件下文章算法较传统算法有着较高的重构概率。
압축감지이론시이용신호적희소성，채용중구산법통과소량적관측치취가이실현대해신호적정학중구。SL0（Smoothed l0）산법시기우l0범수적희소신호중구산법，통과공제삼수축보핍근최우해。침대평활함수적선취문제，문장제출일충신적평활함수서렬근사l0범수，실현희소신호적정학중구。방진결과표명，재상동실험조건하문장산법교전통산법유착교고적중구개솔。
Compressive sensing is a novel signal sampling theory under the condition that the signals are sparse. In this case, the small amount of signal values can be reconstructed accurately.SL0 (Smoothed l0) is a reconstruction algorithm based onl0norm to get the optimal solution by changing parameters. In order to choose an approprite sequence of smoothed functions, we propose a new reconstruction algorithm based a new smoothed function which can get accurate reconstructon. Experimental results show that the proposed algorithm has better probability of reconstructon than other traditional algorithm.