A Complex Mixing Matrix Estimation Algorithm Based on Single Source Points

This paper considers the complex mixing matrix estimation in the under-determined blind source separation. An effective estimation algorithm through detecting single source points contributed by only one source is proposed. First, the single source points are detected by utilizing the real and the imaginary components of the time-frequency coefficients of mixed signals. The algorithm is suitable for the case in which the mixing matrix is complex, while traditional algorithms usually estimate the real mixing matrix. Then, through modeling and calculating, the mixing matrix of mixed signals can be estimated. Finally, the clustering process is improved in order to get more accurate results. The algorithm can estimate the complex mixing matrix when the number of sensors is less than that of sources. The experimental results validate the efficiency of the estimation algorithm.