The errors of approximation for feedforward neural networks in the metric
โ Scribed by Feilong Cao; Rui Zhang
- Publisher
- Elsevier Science
- Year
- 2009
- Tongue
- English
- Weight
- 564 KB
- Volume
- 49
- Category
- Article
- ISSN
- 0895-7177
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๐ SIMILAR VOLUMES
In this paper, we construct two types of feed-forward neural networks (FNNs) which can approximately interpolate, with arbitrary precision, any set of distinct data in the metric space. Firstly, for analytic activation function, an approximate interpolation FNN is constructed in the metric space, an
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 valu