Title :
Similarities of LVQ and RBF learning-a survey of learning rules and the application to the classification of signals from high-resolution electrocardiography
Author :
Schwenker, F. ; Kestler, H.A. ; Palm, G. ; Höher, M.
Author_Institution :
Dept. of Neural Inf. Processing, Ulm Univ., Germany
Abstract :
In this paper algorithms for neural network training are described. We discuss the apparent similarities of LVQ and RBF classification which motivate us to combine the two approaches. The resulting algorithm is then tested on features extracted from signals from high-resolution electrocardiography
Keywords :
electrocardiography; feedforward neural nets; learning (artificial intelligence); pattern classification; vector quantisation; LVQ learning; RBF learning; high-resolution electrocardiography; linear vector quantisation; radial basis functions; signal classification; Artificial neural networks; Biomedical optical imaging; Cardiography; Cognition; Feedforward neural networks; Neural networks; Neurons; Phase estimation; Prototypes; Testing;
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
DOI :
10.1109/ICSMC.1994.399913
