基于双字典集的信号稀疏分解算法

Signal sparse decomposition based on the two dictionary sets

为得到关于信号更为稀疏的表示,提出一种基于双字典集的信号稀疏分解算法。在算法过程中,建立如下两个字典集:已选字典集和待选字典集。该算法以重复加权提升搜索(RWBS)算法为基础,增加了一步更为严格的从待选字典集中选择最佳核函数的过程,故该算法在保留初始算法的优点的同时,可以产生更为稀疏的模型。通过仿真实验和真实数据实验验证了所提算法的性能。

A new sparse decomposition algorithm was presented to get a sparser representation of the signal. In the procedure of the algorithm, it established the two dictionary sets consisting of the selected dictionary set and the unselected dictionary set. The proposed algorithm added a more strict process which selected the best kernel from the unselected dictionary set to the original Repeated Weighted Boosting Search （ RWBS）, so the proposed algorithm could produce a sparser model while reserving the advantages of the original algorithm. The effectiveness of the proposed algorithm is illustrated through several examples.