Abstract
In 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.
Cite
CITATION STYLE
APA
Crippa, P., & Turchetti, C. (2003). Learning of SAINNs from covariance function: Historical learning. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2773 PART 1, pp. 177–183). Springer Verlag. https://doi.org/10.1007/978-3-540-45224-9_26
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