IANN'98

• New Results on Nonlinear PCA Criterion in Blind Source Separation
  J. Karhunen, P. Pajunen
• Collinearity and Parallism are Significant Second Order Relations of Gabor Wavelet Responses
  N. Krüger
• Blind Separation of Convolved Mixtures in the Frequency Domain
  P. Smaragdis
• Blind Source Separation using Algorithmic Information Theory
  P. Pajunen
• Independent Component Analysis in the Presence of Noise: A Maximum Likelihood Approach
  A. Hyvärinen
• Further Results on Nonlinearity and Separation Capability of a Linear Mixture ICA Method and learned Parametric Mixture Algorithm
  L. Xu, C. C. Cheung, S. Amari
• Bayesian Ying-Yang Dependence Reduction Theory and Blind Source Separation on Instantaneous Mixture
  L. Xu
• Independent Component Analysis for Noisy Data
  A. Cichocki, S. C. Douglas, S. Amari, P. Mierzejewski
• How a Neural Network Can Discover Gaussian Clusters
  A. Budillon, M. Corrente, F. Palmieri
• A Neural Network for Blind Separation of Convolved Non-stationary Signals
  M. Kawamoto, A. Kardec Barros, N. Ohnishi
• Adaptive Blind Elimination of Artifacts in ECG Signals
  A. Kardec Barros, A. Mansour, N. Ohnishi
• The Binaural Cocktail Party Effect and Blind Signal Processing
  M. Girolami
• Finding Independent Causes Using Principal Factor Analysis
  D. Charles
• Fuzzy and Neuro-fuzzy HYPAS Controllers Implemented for an Electro-Hydraulic Axis
  F. Ionescu, C. I. Vlad, D. Arotaritei
• ICA Learning Rules: Stationarity, Stability and Sigmoids
  E. Oja