@inproceedings{0eeae7a2043141ad93be304169085c50,
title = "A new method for kurtosis maximization and source separation",
abstract = "This paper introduces a new method to maximize kurtosis-based contrast functions. Such contrast functions appear in the problem of blind source separation of convolutively mixed sources: the corresponding methods recover the sources one by one using a deflation approach. The proposed maximization algorithm is based on the particular nature of the criterion. The method is similar in spirit to a gradient ascent method, but differs in the fact that a {"}reference{"} contrast function is considered at each line search. The convergence of the method to a stationary point of the criterion can be proved. The theoretical result is illustrated by simulation.",
keywords = "Blind source separation, Contrast function, Convergence, Deflation, Higher-order statistics, Optimization, Reference system",
author = "Marc Castella and Eric Moreau",
year = "2010",
month = jan,
day = "1",
doi = "10.1109/ICASSP.2010.5496250",
language = "English",
isbn = "9781424442966",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2670--2673",
booktitle = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings",
note = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 ; Conference date: 14-03-2010 Through 19-03-2010",
}