Nonlinear static and dynamic blind source separation using ensemble learning

Proceedings of the International Joint Conference on Neural Networks

Volumn 4, Issue , 2001, Pages 2750-2755

  Valpola, H ^a   Honkela, A ^a   Karhunen, J ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; PROBABILITY DENSITY FUNCTION; SPEECH; VECTORS;

ENSEMBLE LEARNING; LINEAR PREDICTION TECHNIQUES;

BLIND SOURCE SEPARATION;

EID: 0034861188     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. ICA, graphical models and variational methods
2. Ensemble learning in Bayesian neural networks
3. Fisher scoring and a mixture of modes approach for approximate inference and learning in nonlinear state space models
4. Learning nonlinear dynamical systems using an EM algorithm
5. Nonlinear independent component analysis: Existence and uniqueness results
6. Bayesian nonlinear independent component analysis by multi-layer perceptrons
7. Ensemble learning
8. Ensemble learning for blind source separation
9. An unsupervised ensemble learning method for nonlinear dynamic state-space models