DocumentCode :
2697501
Title :
A learning rule in the Chebyshev norm for multilayer perceptrons
Author :
Burrascano, Pietro ; Lucci, P.
fYear :
1990
fDate :
17-21 June 1990
Firstpage :
81
Abstract :
An L∞ version of the backpropagation paradigm is proposed, and a comparison between the L2 and the L∞ paradigms is presented, taking into account computational cost and speed of convergence. The convergence of the L∞ algorithm has been successfully tested in several cases
Keywords :
convergence; learning systems; neural nets; Chebyshev norm; backpropagation paradigm; computational cost; convergence; learning rule; multilayer perceptrons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/IJCNN.1990.137827
Filename :
5726785
Link To Document :
https://search.ricest.ac.ir/dl/search/defaultta.aspx?DTC=49&DC=2697501
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