Technical Report on Separation Methods for Nonlinear Mixtures

[1]  Motoaki Kawanabe,et al.  Kernel Feature Spaces and Nonlinear Blind Souce Separation , 2001, NIPS.

[2]  L. Almeida,et al.  ICA of linear and nonlinear mixtures based on mutual information , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[3]  M. Girolami,et al.  Advances in Independent Component Analysis , 2000, Perspectives in Neural Computing.

[4]  J. Karhunen,et al.  Building Blocks for Hierarchical Latent Variable Models , 2001 .

[5]  Juha Karhunen,et al.  Hierarchical models of variance sources , 2004, Signal Process..

[6]  Hagai Attias,et al.  Independent Factor Analysis , 1999, Neural Computation.

[7]  A. Honkela.  Speeding up cyclic update schemes by pattern searches , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[8]  Nikunj C. Oza,et al.  Online Ensemble Learning , 2000, AAAI/IAAI.

[9]  Juha Karhunen,et al.  Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches , 2003, Neural Processing Letters.

[10]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[11]  Juha Karhunen,et al.  Final Technical Report on BSS Models and Methods for Non-Independent BSS , 2003 .

[12]  Bernhard Schölkopf,et al.  Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.

[13]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[14]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[15]  L. B. Almeida,et al.  MISEP-an ICA method for linear and nonlinear mixtures, based on mutual information , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[16]  Pierre-Olivier Amblard,et al.  Blind Equalization of a Nonlinear Satellite System Using MCMC Simulation Methods , 2002, EURASIP J. Adv. Signal Process..

[17]  Dinh-Tuan Pham,et al.  Improving algorithm speed in PNL mixture separation and Wiener system inversion , 2003 .

[18]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[19]  Luis B. Almeida,et al.  Faster Training in Nonlinear ICA using MISEP , 2002 .

[20]  Erkki Oja,et al.  Nonlinear dynamical factor analysis for state change detection , 2004, IEEE Transactions on Neural Networks.

[21]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[22]  Luís B. Almeida,et al.  Linear and nonlinear ICA based on mutual information - the MISEP method , 2004, Signal Process..

[23]  Christian Jutten,et al.  A geometric approach for separating post non-linear mixtures , 2002, 2002 11th European Signal Processing Conference.

[24]  Christian Jutten,et al.  Blind Inversion of Wiener System using a minimization-projection (MP) approach , 2003 .

[25]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[26]  L. B. Almeida,et al.  Linear and nonlinear ICA based on mutual information , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[27]  E. Oja,et al.  Independent Component Analysis , 2013 .

[28]  Andrzej Cichocki,et al.  Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications , 2002 .

[29]  Erkki Oja,et al.  DETECTING PROCESS STATE CHANGES BY NONLINEAR BLIND SOURCE SEPARATION , 2003 .

[30]  J. Karhunen,et al.  Nonlinear Independent Factor Analysis by Hierarchical Models , 2003 .

[31]  Dinh Tuan Pham,et al.  BLIND SOURCE SEPARATION IN POST NONLINEAR MIXTURES , 2001 .

[32]  Christian Jutten,et al.  Parametric approach to blind deconvolution of nonlinear channels , 2002, ESANN.

[33]  Juha Karhunen,et al.  Missing Values in Hierarchical Nonlinear Factor Analysis , 2003 .

[34]  Nello Cristianini,et al.  An introduction to Support Vector Machines , 2000 .

[35]  Massoud Babaiezadeh Malmiri.  On blind source separation in convolutive and nonlinear mixtures , 2002 .

[36]  Christian Jutten,et al.  Quasi-nonparametric blind inversion of Wiener systems , 2001, IEEE Trans. Signal Process..

[37]  T. Sejnowski,et al.  Separation of post-nonlinear mixtures using ACE and temporal decorrelation , 2001 .

[38]  Motoaki Kawanabe,et al.  Kernel-Based Nonlinear Blind Source Separation , 2003, Neural Computation.

[39]  Bernhard Schölkopf,et al.  Learning with kernels , 2001 .

[40]  J. Karhunen,et al.  Advances in Nonlinear Blind Source Separation , 2003 .

[41]  Motoaki Kawanabe,et al.  Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation , 2003, J. Mach. Learn. Res..

[42]  Richard M. Everson,et al.  Independent Component Analysis: Principles and Practice , 2001 .

[43]  Christian Jutten,et al.  Source separation in post-nonlinear mixtures , 1999, IEEE Trans. Signal Process..

[44]  E. Oja,et al.  Nonlinear Blind Source Separation by Variational Bayesian Learning , 2003, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[45]  Christian Jutten,et al.  Nonlinear source separation: the post-nonlinear mixtures , 1997, ESANN.

[46]  C. Jutten,et al.  Improving semiconductor-based chemical sensor arrays using advanced algorithms for blind source separation , 2004, ISA/IEEE Sensors for Industry Conference, 2004. Proceedings the.

[47]  C. Jutten,et al.  On the separability of nonlinear mixtures of temporally correlated sources , 2003, IEEE Signal Processing Letters.

[48]  Andrzej Cichocki,et al.  Robust learning algorithm for blind separation of signals , 1994 .