Title :
Time topology for the self-organizing map
Author_Institution :
Neural Networks Res. Centre, Helsinki Univ. of Technol., Hut, Finland
Abstract :
Time information of the input data is used for evaluating the goodness of the self-organizing map to store and represent temporal feature vector sequences. A new node neighborhood is defined for the map which takes the temporal order of the input samples into account. A connection is created between those two map modes which are the best-matching units for two successive input samples in time. This results in the time-topology preserving network
Keywords :
self-organising feature maps; topology; best-matching units; self-organizing map; temporal feature vector sequences; temporal order; time topology; unsupervised learning; Artificial neural networks; Ear; Euclidean distance; Lattices; Network topology; Neural networks; Position measurement; Unsupervised learning;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.832671
