Mixing Matrix Estimation Algorithm for Underdetermined Instantaneous Mixing Model

doi:10.23940/ijpe.19.01.p34.337345

Abstract

Abstract:

Estimating the mixing matrix is a research that focuses on underdetermined blind source separation. In order to get a more accurate estimated mixing matrix, we investigate a novel algorithm for mixing matrix estimation. Firstly, a new method for detecting single source points was introduced. Then, we reckoned the signal quantity and initial clustering centers by adopting an improved clustering method based on the potential function. Finally, the point density theory and the initial clustering centers were utilized to get more accurate clustering centers and estimated the mixing matrix. The simulation results illustrate that we can obtain the more accurate and stable estimation of the mixing matrix by using the proposed algorithm.

Key words: underdetermined blind source separation, mixing matrix estimation, potential function, single source points

Shi Fan and Liu Chuang. Mixing Matrix Estimation Algorithm for Underdetermined Instantaneous Mixing Model [J]. Int J Performability Eng, 2019, 15(1): 337-345.

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