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- W1488854741 abstract "AbstractIn this paper the learning capabilities of a class of neural networks named Stochastic Approximate Identity Neural Networks (SAINNs) have been analyzed. In particular these networks are able to approximate a large class of stochastic processes from the knowledge of their covariance function.KeywordsNeural NetworkCovariance FunctionInverse Fourier TransformCanonical RepresentationApproximate IdentityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W1488854741 created "2016-06-24" @default.
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- W1488854741 date "2003-01-01" @default.
- W1488854741 modified "2023-09-24" @default.
- W1488854741 title "Learning of SAINNs from Covariance Function: Historical Learning" @default.
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- W1488854741 doi "https://doi.org/10.1007/978-3-540-45224-9_26" @default.
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