Temporal minimum entropy and minimum mutual information criteria of nonstationary signals for blind source separation
Hsiao‐Chun Wu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
The information-theoretic network for independent component analysis has been studied for unsupervised learning in the signal processing area. We derive a learning rule from the mutual information or the sum of the marginal entropy based on the local-Gaussian assumption for blind source separation of the convolutive mixture. The algorithm has been tested for several real-world recordings and showed the promising results.