Generalized radial basis function networks for classification and novelty detection: Self-organization of optimal Bayesian decision

Neural Networks

Volumn 13, Issue 10, 2000, Pages 1075-1093

  Albrecht, S ^a   Busch, J ^a   Kloppenburg, M ^a   Metze, F ^a   Tavan, P ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

Classification; Generalized radial basis functions; Maximum likelihood density estimation; Self organization

Indexed keywords

ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; DATA STRUCTURES; DECISION THEORY; HIERARCHICAL SYSTEMS; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY DENSITY FUNCTION; SIGNAL DETECTION; SIMULATED ANNEALING;

EXPECTATION-MAXIMIZATION ALGORITHMS; RADIAL BASIS FUNCTION NETWORKS; SELF-ORGANIZATION THEORY;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; CLASSIFICATION; DECISION MAKING; LEARNING; MULTIVARIATE ANALYSIS; NERVE CELL; ORGANIZATION; PRIORITY JOURNAL; PROBABILITY; RECEPTIVE FIELD; SELF ORGANIZATION; SPEECH DISCRIMINATION; STOCHASTIC MODEL; TRAINING;

EID: 0034552537     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(00)00060-5     Document Type: Article

References (43)

1. Approximation capability to functions of several variables, nonlinear functionals, and operators by radial basis function neural networks
2. The recent excitement about neural networks
3. Maximum likelihood from incomplete data via the EM algorithm
4. Asymptotic level density in topological feature maps
5. Cooling schedules for learning in neural networks
6. Topological feature maps with self-organized lateral connections: a population-coded one-layer model of associative memory
7. Convergence analysis of local feature extraction algorithms
8. Deterministic annealing for density estimation by multivariate normal mixtures
9. Self-organized formation of topologically correct feature maps
10. Radial basis function networks and complexity regularization in function learning
11. Least squares quantization in PCM
12. Some methods for classification and analysis of multivariate observations
13. Neural-gas network for vector quantization and its application to time-series prediction
14. A 'neural-gas' network learns topologies
15. Combined learning and use for a mixture model equivalent to the RBF classifier
16. Fast learning in networks of locally tuned processing units
17. A mean field theory algorithm for neural networks
18. Networks for approximation and learning
19. Regularization algorithms for learning that are equivalent to multilayer networks
20. Statistical mechanics and phase transitions in clustering
21. Development of feature detectors by self-organization
22. A self-organizing network for principal-component analysis
23. A general regression neural network
24. Maximum likelihood training of probabilistic neural networks
25. Supervised and unsupervised learning in radial basis function classifiers
26. Self-organization of associative memory and pattern classification: recurrent signal processing on topological feature maps
27. A neural network approach to statistical pattern classification by semiparametric estimation of probability density functions
28. How patterned neural connections can be set up by self-organization
29. On radial basis function nets and kernel regression: statistical consistency, convergence rates, and receptive fields
30. Robust maximum likelihood training of heteroscedastic probabilitic neural networks