Skip to Main Content

Advertisement

Umbrella Alt Text
header search
Search
Advanced Search
Skip Nav Destination

Faithful Representation of Separable Distributions

Neural Computation (1997) 9 (6): 1305–1320.
This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.
Semi-blind source separation for the estimation of the clay content over semi-vegetated areas using VNIR/SWIR hyperspectral airborne data
  • W. Ouerghemmi
  • C. Gomez
  • S. Naceur
  • P. Lagacherie
Remote Sensing of Environment (2016) 181: 251.
Expectation–maximisation approach to blind source separation of nonlinear convolutive mixture
  • J. Zhang
  • S.S. Dlay
  • W.L. Woo
IET Signal Processing (2007) 1 (2): 51.
Monitoring the Formation of Kernel-Based Topographic Maps in a Hybrid SOM-kMER Model
IEEE Transactions on Neural Networks (2006) 17 (5): 1336.
Historical data analysis based on plots of independent and parallel coordinates and statistical control limits
  • Hamza Albazzaz
  • Xue Z. Wang
Journal of Process Control (2006) 16 (2): 103.
Nonlinear blind source separation using a hybrid RBF-FMLP network
  • W.L. Woo
  • S.S. Dlay
IEE Proceedings - Vision, Image, and Signal Processing (2005) 152 (2): 173.
Flexible Parametrization of Postnonlinear Mixtures Model in Blind Sources Separation
  • D.-T. Pham
IEEE Signal Processing Letters (2004) 11 (6): 533.
ADVANCES IN BLIND SOURCE SEPARATION (BSS) AND INDEPENDENT COMPONENT ANALYSIS (ICA) FOR NONLINEAR MIXTURES
  • CHRISTIAN JUTTEN
  • JUHA KARHUNEN
International Journal of Neural Systems (2004) 14 (05): 267.
Kernel-Based Nonlinear Blind Source Separation
  • Stefan Harmeling
  • Andreas Ziehe
  • Motoaki Kawanabe
  • Klaus-Robert Müller
Neural Computation (2003) 15 (5): 1089.
Natural Discriminant Analysis Using Interactive Potts Models
  • Jiann-Ming Wu
Neural Computation (2002) 14 (3): 689.
Learning generative models of natural images
  • Jiann-Ming Wu
  • Zheng-Han Lin
Neural Networks (2002) 15 (3): 337.
Separation of sources using simulated annealing and competitive learning
  • C.G. Puntonet
  • A. Mansour
  • C. Bauer
  • E. Lang
Neurocomputing (2002) 49 (1-4): 39.
Top-down attention to complement independent component analysis for blind signal separation
  • Un-Min Bae
  • Hyung-Min Park
  • Soo-Young Lee
Neurocomputing (2002) 49 (1-4): 315.
Frontiers of research in BSS/ICA
  • V.David Sánchez A
Neurocomputing (2002) 49 (1-4): 7.
Underdetermined blind source separation using sparse representations
  • Pau Bofill
  • Michael Zibulevsky
Signal Processing (2001) 81 (11): 2353.
Independent component analysis using Potts models
IEEE Transactions on Neural Networks (2001) 12 (2): 202.
LOCAL LINEAR INDEPENDENT COMPONENT ANALYSIS BASED ON CLUSTERING
  • JUHA KARHUNEN
  • SIMONA MĂlĂROIU
  • MIKA ILMONIEMI
International Journal of Neural Systems (2000) 10 (06): 439.
A unifying information-theoretic framework for independent component analysis
  • Te-Won Lee
  • M. Girolami
  • A.J. Bell
  • T.J. Sejnowski
Computers & Mathematics with Applications (2000) 39 (11): 1.
Faithful representations with topographic maps
  • M.M. Van Hulle
Neural Networks (1999) 12 (6): 803.
Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources
  • Te-Won Lee
  • Mark Girolami
  • Terrence J. Sejnowski
Neural Computation (1999) 11 (2): 417.
Kernel-Based Equiprobabilistic Topographic Map Formation
  • Marc M. Van Hulle
Neural Computation (1998) 10 (7): 1847.
Information–theoretic approach to blind separation of sources in non-linear mixture
  • Howard Hua Yang
  • Shun-ichi Amari
  • Andrzej Cichocki
Signal Processing (1998) 64 (3): 291.
Spatial Decorrelation in Orientation-Selective Cortical Cells
  • Alexander Dimitrov
  • Jack D. Cowan
Neural Computation (1998) 10 (7): 1779.
A First Application of Independent Component Analysis to Extracting Structure from Stock Returns
  • Andrew D. Back
  • Andreas S. Weigend
International Journal of Neural Systems (1997) 08 (04): 473.

Advertisement

  • Online ISSN 1530-888X
  • Print ISSN 0899-7667
A product of The MIT Press
Newsletter Sign Up

MIT Press Direct

Information

MIT Press

Contact Us

© 2023 The MIT Press
Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal
This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy. No content on this site may be used to train artificial intelligence systems without permission in writing from the MIT Press.
Accept