计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
14期
212-216
,共5页
奇异值分解%混合矩阵%稀疏信号%势函数%聚类
奇異值分解%混閤矩陣%稀疏信號%勢函數%聚類
기이치분해%혼합구진%희소신호%세함수%취류
singular value decomposition%mixing matrix%sparse signal%potential function%clustering
针对稀疏信号盲源分离势函数法需要过多参数，以及聚类算法需要知道源信号个数的缺陷，采用基于拉普拉斯模型的势函数法估计源信号数目和混合矩阵。将混合信号重新聚类，对每一类信号的协方差矩阵进行奇异值分解，混合矩阵得到更精确的估计，进而源信号也得到更精确的估计。通过计算机仿真，表明了该算法的优越性。
針對稀疏信號盲源分離勢函數法需要過多參數，以及聚類算法需要知道源信號箇數的缺陷，採用基于拉普拉斯模型的勢函數法估計源信號數目和混閤矩陣。將混閤信號重新聚類，對每一類信號的協方差矩陣進行奇異值分解，混閤矩陣得到更精確的估計，進而源信號也得到更精確的估計。通過計算機倣真，錶明瞭該算法的優越性。
침대희소신호맹원분리세함수법수요과다삼수，이급취류산법수요지도원신호개수적결함，채용기우랍보랍사모형적세함수법고계원신호수목화혼합구진。장혼합신호중신취류，대매일류신호적협방차구진진행기이치분해，혼합구진득도경정학적고계，진이원신호야득도경정학적고계。통과계산궤방진，표명료해산법적우월성。
For the defects that blind source separation potential function method requires too many parameters and the number of the source signal needs to be known as priori condition in the clustering algorithm, the potential function method based on Lapla-cian model is used to estimate the number of source signals and the mixing matrix. Then the mixed signals are re-clustered, and the covariance matrix of each type of signal is solved with the singular value decomposition. The mixing matrix is estimated more precisely, and then the source signals are also estimated more precisely. Through computer simulation, it demonstrates the superiority of the proposed algorithm.
