摘要
该文研究基于Matching Pursuit(MP)方法实现的信号稀疏分解算法,通过对信号稀疏分解中使用的过完备原子库结构特性的分析,提出了一种新的信号稀疏分解算法。该算法首先通过利用原子库的结构特性,很好地处理了稀疏分解过程中计算量和存储量之间的关系。在此基础上,把信号稀疏分解中计算量很大的内积运算转换成互相关运算,最后用FFT实现互相关运算,从而大大提高了信号稀疏分解的速度。算法的有效性为实验结果所证实。
In this paper, after study of Matching Pursuit （MP） based signal sparse decomposition, a new sparse decomposition algorithm is presented based on analysis of structure property of the over-complete atom dictionary used in signal sparse decomposition. By making use of the structure property, firstly this new algorithm balances very well computer＇s speed and memory. Then this algorithm converts very time-consuming inner product calculations in sparse decomposition into crosscorrelation calculations that are fast done by FFT. Therefore the new algorithm improves a lot the speed of signal sparse decomposition. Finally the experimental results show that the performance of the proposed algorithm is very good.
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第4期614-618,共5页
Journal of Electronics & Information Technology
基金
教育部留学回国人员科研启动基金资助课题
