Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Blind separation of sources, Part II: problems statement
Signal Processing
Blind separation of sources, Part III: stability analysis
Signal Processing
Blind Source Separation and Equiprobabilistic Topographic Maps
Journal of VLSI Signal Processing Systems
Applying Neural Networks and Genetic Algorithms to the Separation of Sources
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Neural Network Based Blind Source Separation of Non-linear Mixtures
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A Functional-Neural Network for Post-Nonlinear Independent Component Analysis
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Image denoising using self-organizing map-based nonlinear independent component analysis
Neural Networks - New developments in self-organizing maps
Kernel-based nonlinear blind source separation
Neural Computation
Misep—linear and nonlinear ICA based on mutual information
The Journal of Machine Learning Research
Linear and nonlinear ICA based on mutual information: the MISEP method
Signal Processing - Special issue on independent components analysis and beyond
MISEP - Linear and nonlinear ICA based on mutual information
The Journal of Machine Learning Research
A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold
Neural Computation
MISEP Method for Postnonlinear Blind Source Separation
Neural Computation
A histogram based data-reducing algorithm for the fixed-point independent component analysis
Pattern Recognition Letters
Neural-Based Separating Method for Nonlinear Mixtures
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Initialisation of Nonlinearities for PNL and Wiener systems Inversion
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
An Independent Component Analysis Evolution Based Method for Nonlinear Speech Processing
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Unsupervised learning with stochastic gradient
Neurocomputing
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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In many signal processing applications, the signals provided by the sensors are mixtures of many sources. The problem of separation of sources is to extract the original signals from these mixtures. A new algorithm, based on ideas of back propagation learning, is proposed for source separation. No a priori information on the sources themselves is required, and the algorithm can deal even with nonlinear mixtures. After a short overview of previous works in that field, we will describe the proposed algorithm, then some experimental results will be discussed.