DocumentCode
314381
Title
On the importance of sorting in “neural gas” training of vector quantizers
Author
Ancona, Fabio ; Ridella, Sandro ; Rovetta, Stefano ; Zunino, Rodolfo
Author_Institution
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Volume
3
fYear
1997
fDate
9-12 Jun 1997
Firstpage
1804
Abstract
The paper considers the role of the sorting process in the well-known “neural gas” model for vector quantization. Theoretical derivations and experimental evidence show that complete sorting is not required for effective training, since limiting the sorted list to even a few top units performs effectively. This property has a significant impact on the implementation of the overall neural model at the local level
Keywords
learning (artificial intelligence); neural nets; sorting; vector quantisation; local level model; neural gas training; neural model; sorting; vector quantizers; Clustering algorithms; Computational efficiency; Electronic switching systems; Hardware; Information representation; Iterative algorithms; Neurons; Sorting; Testing; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.614171
Filename
614171
Link To Document