Autoregressive signal separation approach with seesaw-mapping technique on temporal source separation

Most existing independent component analysis approaches are proposed for blind signal separation under the assumption that the sources are independently and identically distributed signals. However, the real signals are often temporal correlated in a certain degree. In our previous paper (1999), we have presented an autoregressive signal separation approach (ASSA) for AR(p) temporal signal separation, where we assume the noises in AR source signals are non-Gaussian. In this paper, we further study this approach under the Gaussian noises in AR sources with the seesaw-mapping technique. Experiments demonstrated that the seesaw-mapping technique can be applied successfully to the ASSA approach