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ORCIDNeurocomputing, Volume 22
Volume 22, Number 1-3, November 1998
- Juha Karhunen, Petteri Pajunen, Erkki Oja:
The nonlinear PCA criterion in blind source separation: Relations with other approaches. 5-20 - Paris Smaragdis:
Blind separation of convolved mixtures in the frequency domain. 21-34 - Petteri Pajunen:
Blind source separation using algorithmic information theory. 35-48 - Aapo Hyvärinen:
Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood. 49-67 - Lei Xu, Chi Chiu Cheung, Shun-ichi Amari:
Learned parametric mixture based ICA algorithm. 69-80 - Lei Xu:
Bayesian Kullback Ying-Yang dependence reduction theory. 81-111 - Andrzej Cichocki
, Scott C. Douglas, Shun-ichi Amari:
Robust techniques for independent component analysis (ICA) with noisy data. 113-129 - Francesco Palmieri, Alessandra Budillon, Michele Calabrese, Davide Mattera:
Searching for a binary factorial code using the ICA framework. 131-144 - Darryl Charles:
Constrained PCA techniques for the identification of common factors in data. 145-156 - Mitsuru Kawamoto, Kiyotoshi Matsuoka, Noboru Ohnishi:
A method of blind separation for convolved non-stationary signals. 157-171 - Allan Kardec Barros, Ali Mansour, Noboru Ohnishi:
Removing artifacts from electrocardiographic signals using independent components analysis. 173-186 - Erkki Oja:
From neural learning to independent components. 187-199 - Mark A. Girolami:
A nonlinear model of the binaural cocktail party effect. 201-215
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