Title :
Dynamics of clustering multiple backpropagation networks
Author :
Lincoln, William P. ; Skrzypek, Josef
Author_Institution :
Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA
Abstract :
It is known that synergistic effects of clustering multiple backpropagation nets improves supervised learning, generalization, fault tolerance, and self-organization with respect to a comparably complex nonclustered system. A model that captures the underlying reasons for the synergy of clustering is outlined. The underlying ideas can apply to any net trained with a supervised learning rule
Keywords :
dynamics; learning systems; neural nets; clustering multiple backpropagation networks; dynamics; fault tolerance; learning systems; neural nets; self-organization; supervised learning rule; Backpropagation; Computer science; Convergence; Degradation; Error correction; Fault tolerance; Fault tolerant systems; Laboratories; Supervised learning;
Conference_Titel :
Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
0-87942-597-0
DOI :
10.1109/ICSMC.1990.142134
