@inproceedings{bf6ef7be0e554df6a1aec040e6fb60f6,
title = "MIMO-AR system identification and blind source separation using GMM",
abstract = "The problem of blind source separation (BSS) for multiple-input multiple-output (MIMO) autoregressive (AR) mixtures is addressed in this paper. A new time-domain method for system identification and BSS is proposed based on the Gaussian mixture model (GMM) for sources distribution. The algorithm is based on the generalized expectation-maximization (GEM) method for joint estimation of the AR model parameters and the GMM parameters of the sources. The method is tested via simulations of synthetic and real audio signals. The results show that the proposed algorithm outperforms the well-known multidimensional linear predictive coding (LPC), and it achieves higher signal-to-interference ratio (SIR) in the BSS problem.",
keywords = "BSS, Convolutive mixtures, EM, GMM, MIMO system identification, MIMO-AR",
author = "Tirza Routtenberg and Joseph Tabrikian",
year = "2007",
month = jan,
day = "1",
doi = "10.1109/ICASSP.2007.366791",
language = "English",
isbn = "1424407281",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "761--764",
booktitle = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07",
address = "United States",
note = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 ; Conference date: 15-04-2007 Through 20-04-2007",
}