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Universal approximation with error bounds for dynamic artificial neural network models: A tutorial and some new results.
Kwang Ki Kevin Kim
Ernesto Rios-Patron
Richard D. Braatz
Published in:
CACSD (2011)
Keyphrases
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error bounds
theoretical analysis
worst case
artificial neural network models
decision trees
dynamic environments
data sets
neural network
polynomial time approximation
machine learning
similarity measure
objective function
upper bound
approximation algorithms