Abstract
In order to learn a nonlinear target function, a neural network uses activation functions which are nonlinear. The choice of each specific activation function defines different types of neural networks.
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- 1.
This follows Schwartz’s distribution theory.
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Calin, O. (2020). Activation Functions. In: Deep Learning Architectures. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-36721-3_2
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DOI: https://doi.org/10.1007/978-3-030-36721-3_2
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Online ISBN: 978-3-030-36721-3
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