Journal
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
Volume 417, Issue 2, Pages 963-969Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmaa.2014.03.092
Keywords
Neural network; MLP model; Sigmoidal function; Approximation; Superposition
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Funding
- SOCAR Science Foundation of Azerbaijan [SOCAR EF 2013]
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In the current note, we show that a two hidden layer neural network with d inputs, d neurons in the first hidden layer, 2d+2 neurons in the second hidden layer and with a specifically constructed sigmoidal and infinitely differentiable activation function can approximate any continuous multivariate function with arbitrary accuracy. (C) 2014 Elsevier Inc. All rights reserved.
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