DocumentCode :
285287
Title :
A modular system which improves the topological maps
Author :
Schwenk, H. ; Gallinari, P. ; Driancourt, X.
Author_Institution :
CNRS URA Lab. de Recherches en Inf., Univ. de Paris Sud, Orsay, France
Volume :
3
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
352
Abstract :
A system which permits the cooperation of a linear network with a topological map (TM) is proposed. It allows drastic reduction of the computing time for the TM. It is shown that the TM can be expressed as an adaptive gradient algorithm for the minimization of a cost function. Then, to train the hybrid architecture, new cost functions and algorithms are proposed. Convergence issues are discussed which allow considerations of generic problems in the general framework of multimodule architectures, and solutions are proposed. Some tests which illustrate the behavior and performance of the algorithms are presented
Keywords :
self-organising feature maps; adaptive gradient algorithm; cost function minimisation; generic problems; hybrid architecture; linear network; modular system; multimodule architectures; topological maps; Adaptive algorithm; Adaptive systems; Computational complexity; Computer architecture; Cost function; Data structures; Image processing; Neural networks; Partitioning algorithms; Speech processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227149
Filename :
227149
Link To Document :
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