Blind speech signal separation based on cumulant approach

One of the proposed methods for separating several speech signals, which are combined in receivers, is the use of blind source separation (BSS) methods. Resource blind separation is the separation and estimation of signals generated by sources in an unknown channel and their combinations received at receivers. Existing algorithms for blind source separation are often based on the special analysis of fourth-order cumulative matrices. However, when cumulative matrices have close eigenvalues, their eigenvectors become very sensitive to the error in estimating the matrices. In this paper, we try to reduce this sensitivity by using a new algorithm and obtain a more accurate estimate.