Convergence analysis of rival penalized competitive learning (RPCL) algorithm

Proceedings of the International Joint Conference on Neural Networks

Volumn 2, Issue , 2002, Pages 1596-1601

  Ma, Jinwen ^a   Wang, Taijun ^a   Xu, Lei ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; LEARNING SYSTEMS; PROBLEM SOLVING; VECTOR QUANTIZATION; VECTORS;

BAYESIAN YING YANG HARMONY LEARNING; RIVAL PENALIZED COMPETITIVE LEARNING ALGORITHM; WEIGHT VECTORS;

LEARNING ALGORITHMS;

EID: 0036079846     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Feature discovery by competitive learning
2. Competitive learning: From iterative activation to adaptive resonance
3. Counterpropagation networks
4. Rival penalized competitive learning for clustering analysis, RBF net, and curve detection
5. A reinforcement learning approach to online clustering
6. Fast image vector quantization using a modified competitive learning neural network approach
7. Radial basis function network configuration using genetic algorithms
8. Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment
9. Bayesian-Kullback Ying-Yang machine: Reviews and new results
10. Rival penalized competitive learning, finite mixture, and multisets clustering
11. Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models
12. An overview on unsupervised learning from data mining perspective
13. YING-YANG machine: A Bayesian-Kullback scheme for unified learning and new results on vector quantization, Keynote talk
14. A cost function approach for rival penalized competitive learning (RPCL)