Title :
Cascaded approach for microsleep data extraction
Author :
Leong, Wai Yie ; Mandic, Danilo P.
Author_Institution :
Dept. of Electron. & Electr. Eng., Imperial Coll. London, London
fDate :
March 31 2008-April 4 2008
Abstract :
The noisy component extraction (NoiCE) algorithm is proposed to blind-extract noisy signals. This is achieved based on a combination of blind extraction structure and a cascaded nonlinear adaptive estimation. Although we use the concept of sequential blind extraction of sources and independent component analysis (ICA), we do not assume that sources are statistically independent. In fact, we show that the proposed cascaded nonlinear filter can be used to extract a signal (a single signal each time) from their noisy mixtures. Computer simulations confirm the validity and performance of the proposed algorithm in noisy microsleep events.
Keywords :
blind source separation; independent component analysis; nonlinear filters; signal denoising; blind extraction structure; blind-extract noisy signals; cascaded nonlinear filter; computer simulations; independent component analysis; microsleep data extraction; noisy component extraction; nonlinear adaptive estimation; sequential blind extraction; Adaptive estimation; Blind source separation; Computer simulation; Cost function; Data mining; Educational institutions; Independent component analysis; Large-scale systems; Nonlinear filters; Source separation; Blind source separation; adaptive cascaded nonlinear estimation; blind source extraction; noisy mixtures;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4518042