Blind separation of circularly distributed sources by neural extended APEX algorithm

Neurocomputing

Volumn 34, Issue 1-4, 2000, Pages 239-252

  Fiori, Simone ^a  

^a UNIVERSITY OF PERUGIA   (Italy)

Author keywords

APEX algorithm; Blind separation of complex valued sources; Hebbian learning; Rayleigh probability distribution

Indexed keywords

COMPUTER SIMULATION; FUNCTIONS; LEARNING SYSTEMS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

BLIND SEPARATION; COMPLEX VALUED SOURCES; HEBBIAN LEARNING; RAYLEIGH PROBABILITY DISTRIBUTION; SUDJIANTO-HASSOUN INTERPRETATION;

APPLICATIONS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; CONTROLLED STUDY; LEARNING; LINEAR SYSTEM; MATHEMATICAL ANALYSIS; NONLINEAR SYSTEM; PRIORITY JOURNAL; THEORY;

EID: 0034284029     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(00)00161-2     Document Type: Article

References (25)

1. Independent component analysis, a survey of some algebraic methods
2. Equivariant adaptive source separation
3. High resolution adaptive bearing estimation using a complex-weighted neural network
4. Adaptive learning algorithm for principal component analysis with partial data
5. Independent component analysis, a new concept?
6. Improved contrast dedicated to blind separation in communications
7. A complex valued Hebbian learning algorithm
8. Complex ICA applied to the separation of radar signals
9. A signal subspace approach for speech enhancement
10. 'Mechanical' neural learning for blind source separation
11. An experimental comparison of three PCA neural networks
12. Independent component analysis by general non-linear Hebbian-like rules
13. Optimization criteria and nonlinear PCA neural networks
14. Representation and separation of signals using nonlinear PCA type learning
15. Generalizations of PCA, optimization problems, and neural networks
16. Nonlinear PCA type learning for source separation and independent component analysis
17. Blind source separation of real world signals
18. Tracking directions-of-arrival with invariant subspace updating
19. Higher order contrasts for self-adaptive source separation
20. Anti-Hebbian learning in topologically constrained linear networks: A tutorial
21. A self-organizing network for Principal-Component Analysis
22. Optimal unsupervised learning in a single-layer linear feedforward neural network
23. Non-linear Hebbian rule: A statistical interpretation
24. Blind separation of convolved sources based on information maximization