Approximation of functions from Korobov spaces by deep convolutional neural networks

Autor: Tong Mao, Ding-Xuan Zhou
Rok vydání: 2022
Předmět:
Zdroj: Advances in Computational Mathematics. 48
ISSN: 1572-9044
1019-7168
DOI: 10.1007/s10444-022-09991-x
Popis: The efficiency of deep convolutional neural networks (DCNNs) has been demonstrated empirically in many practical applications. In this paper, we establish a theory for approximating functions from Korobov spaces by DCNNs. It verifies rigorously the efficiency of DCNNs in approximating functions of many variables with some variable structures and their abilities in overcoming the curse of dimensionality.
Databáze: OpenAIRE
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