DocumentCode
2748675
Title
A clustering algorithm by deterministic annealing and its global convergence
Author
Zhang, Zhihua ; Zheng, Naming ; Shi, Gang
Author_Institution
Inst. of Artificial Intelligence, Xi´´an Jiaotong Univ., China
Volume
3
fYear
2000
fDate
2000
Firstpage
1546
Abstract
The deterministic annealing (DA) is a useful approach to clustering and related optimization problems. With a view to the optimization problem, the clustering algorithm by DA is reformulated in this paper. An important global convergence theorem about this clustering algorithm has been proved
Keywords
convergence; optimisation; pattern clustering; simulated annealing; DA; clustering algorithm; deterministic annealing; global convergence; global convergence theorem; Artificial intelligence; Clustering algorithms; Computational modeling; Convergence; Data analysis; Partitioning algorithms; Prototypes; Relaxation methods; Simulated annealing; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-5747-7
Type
conf
DOI
10.1109/ICOSP.2000.893394
Filename
893394
Link To Document