CAJ | 학술논문

针对源信号的稀疏性影响欠定混合矩阵的估计精度，在源信号单源频率及非单源频率分量分析的基础上，通过对观测信号频率峰值的幅值比值所构成的列向量聚类，提出欠定条件下弱稀疏源信号混合矩阵的盲估计方法。鉴于经典聚类算法的局部收敛性带来聚类结果的不稳定性，采用全局收敛特性较好的遗传模拟退火聚类算法提高聚类结果的鲁棒性。仿真实验表明，本文提出的混合矩阵估计方法及采用的聚类算法在不同欠定条件及噪声环境下具有较强的估计性能。
침대원신호적희소성영향흠정혼합구진적고계정도，재원신호단원빈솔급비단원빈솔분량분석적기출상，통과대관측신호빈솔봉치적폭치비치소구성적렬향량취류，제출흠정조건하약희소원신호혼합구진적맹고계방법。감우경전취류산법적국부수렴성대래취류결과적불은정성，채용전국수렴특성교호적유전모의퇴화취류산법제고취류결과적로봉성。방진실험표명，본문제출적혼합구진고계방법급채용적취류산법재불동흠정조건급조성배경하구유교강적고계성능。
The estimation accuracy of the mixing matrix is influenced by the sources sparsity in the under‐determined mixtures .Based on the analytical results of the single and non‐single frequencies for source signals ,through clustering the column vectors composed by the ratios between the observation signal fre‐quency amplitudes ,a new method for the mixing matrix estimation is proposed when the sources are little sparse to each other .Considering the non‐stability brought by the partial convergence of the classical clustering algorithm ,the genetic and simulated annealing clustering algorithm possessing the global con‐vergence characteristic is used to prove the robustness of the clustering result .The experiment results show that the proposed estimation method and the clustering algorithm can provide good estimation per‐formance under different underdetermined conditions and different noises .