Orthogonal considerations in the design of neural networks for function approximation

B. Francois

Mathematics and Computers in Simulation (MATCOM), 1996, vol. 41, issue 1, 95-108

Abstract: Two problems occur in the design of feedforward neural networks: the choice of the optimal architecture and the initialization. Generally, input and output data of a system (or a function) are measured and recorded. Then, experimenters wish to design a neural network to map exactly these output values.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:41:y:1996:i:1:p:95-108

DOI: 10.1016/0378-4754(95)00062-3

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