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