Estimating the number of sources using independent component analysis

Estimating the number of sources using independent component analysis

1. Introduction Estimating the number of sources provides useful information for signal processing applications, such as blind source separation (BSS) in the frequency domain [1]. It is well known that the number of dominant eigenvalues of the spatial correlation matrix corresponds to the number of sources [2,3]. However, it is difficult to distinguish dominant eigenvalues from the other eigenv...

Estimating the Number of Wideband Radio Sources

In this paper, a new approach for estimating the number of wideband sources is proposed which is based on RSS or ISM algorithms. Numerical results show that the MDL-based and EIT-based proposed algorithm havea much better detection performance than that in EGM and AIC cases for small differences between the incident angles of sources. In addition, for similar conditions, RSS algorithm offers hi...

estimating the number of wideband radio sources

in this paper, a new approach for estimating the number of wideband sources is proposed which is based on rss or ism algorithms. numerical results show that the mdl-based and eit-based proposed algorithm havea much better detection performance than that in egm and aic cases for small differences between the incident angles of sources. in addition, for similar conditions, rss algorithm offers hi...

​Rank based Least-squares Independent Component Analysis

  In this paper, we propose a nonparametric rank-based alternative to the least-squares independent component analysis algorithm developed. The basic idea is to estimate the squared-loss mutual information, which used as the objective function of the algorithm, based on its copula density version. Therefore, no marginal densities have to be estimated. We provide empirical evaluation of th...

Estimating the Number of Sources in Magnetoencephalography