Blind separation of convolutive mixtures of cyclostationary sources.pdf (310.11 kB)
Blind separation of convolutive mixtures of cyclostationary sources using an extended natural gradient method
conference contribution
posted on 2010-02-05, 15:17 authored by Wenwu Wang, Maria G. Jafari, Saeid Sanei, Jonathon ChambersAn on-line adaptive blind source separation algorithm for
the separation of convolutive mixtures of cyclostationary
source signals is proposed. The algorithm is derived by applying natural gradient iterative learning to the novel cost
function which is defined according to the wide sense cyclostationarity
of signals. The efficiency of the algorithm
is supported by simulations, which show that the proposed
algorithm has improved performance for the separation of
convolved cyclostationary signals in terms of convergence
speed and waveform similarity measurement, as compared
to the conventional natural gradient algorithm for convolutive
mixtures.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Citation
WANG, W. ... et al., 2003. Blind separation of convolutive mixtures of cyclostationary sources using an extended natural gradient method. IN: Proceedings of 2003 7th International Symposium on Signal Processing and Its Applications (ISSPA 2003), Paris, France, 1-4 July, Vol. 2, pp. 93-96.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2003Notes
This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.ISBN
0-7803-7946-2Language
- en