An iterative algorithm for entropy regularized likelihood learning on Gaussian mixture with automatic model selection

Neurocomputing

Volumn 69, Issue 13-15, 2006, Pages 1674-1677

  Lu, Zhiwu ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Gaussian mixture; Model selection; Regularization theory

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; ITERATIVE METHODS; MATHEMATICAL MODELS; PARAMETER ESTIMATION;

AUTOMATIC MODEL SELECTION; ENTROPY REGULARIZED LIKELIHOOD; GAUSSIAN MIXTURE; ITERATIVE ALGORITHM;

LEARNING SYSTEMS;

ALGORITHM; ANALYTICAL PARAMETERS; ARTICLE; AUTOMATION; CLASSIFICATION; CONTROLLED STUDY; ENTROPY; IRIS; LEARNING; NORMAL DISTRIBUTION; PRIORITY JOURNAL; PROCESS MODEL; SIMULATION; STATISTICAL MODEL; THEORY;

EID: 33745202405     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2006.01.001     Document Type: Article

References (7)

1. Akaike H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19 6 (1974) 716-723
2. Dennis D.C., and Finbarr O.S. Asymptotic analysis of penalized likelihood and related estimators. Ann. Statist. 18 6 (1990) 1676-1695
3. Z. Lu, An iterative entropy regularized likelihood learning algorithm for cluster analysis with the number of clusters automatically detected, in: Proceedings of the ICNN&B'05, Beijing, China, 2005, pp. 650-655.
4. Ma J., and He Q.C. A Dynamic merge-or-split learning algorithm on Gaussian mixture for automated model selection. Proceedings of the IDEAL'05, Lecture Notes in Computer Science vol. 3578 (2005), Springer, Berlin 203-210
5. Ma J., Wang T., and Xu L. A gradient BYY harmony learning rule on Gaussian mixture with automated model selection. Neurocomputing 56 (2004) 481-487
6. Render R.A., and Walker H.F. Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev. 26 2 (1984) 195-239
7. Xu L. BYY harmony learning, structural RPCL, and topological self-organizing on mixture modes. Neural Networks 15 8-9 (2002) 1231-1237