Title :
A neural network model for real-time adaptive clustering
Author_Institution :
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
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;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298592
