DocumentCode
1903495
Title
A neural network model for real-time adaptive clustering
Author
Fu, LiMin
Author_Institution
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
fYear
1993
fDate
1993
Firstpage
413
Abstract
A neural network model for cluster analysis is presented. The number of cluster need not be predefined. The algorithm is fast and robust. The results are reported from the domain of measuring the antigenic properties of blood samples. Its relations to other clustering alternatives are discussed. The technique is validated statistically with respect to self-consistency
Keywords
blood; image recognition; medical image processing; neural nets; antigenic properties; blood samples; cluster analysis; neural network model; real-time adaptive clustering; self-consistency; Artificial neural networks; Blood; Clustering algorithms; Computational and artificial intelligence; Computational modeling; Computer networks; Information analysis; Neural networks; Neurons; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298592
Filename
298592
Link To Document