Mar 29, 2023 · Our results yield the first quantitative approximation bounds for CVNNs that apply to a wide class of activation functions including the popular modReLU and ...
The present paper shows that a comparable result holds in the setting of complex-valued networks, by proving that one can approximate every function in Ck (Ωn; ...
Sep 21, 2023 · This paper studies the approximation power of complex-valued neural networks (CVNNs). They derive that the approximation error is with the order ...
May 30, 2024 · Under a natural continuity assumption, we show that this rate is optimal; we further discuss the optimality when dropping this assumption.
Abstract: We generalize the classical universal approximation theorem for neural networks to the case of complex-valued neural networks. Precisely, we.
We generalize the classical universal approximation theorem for neural networks to the case of complex-valued neural networks.
Jun 18, 2021 · What do you think about Complex Valued Neural Networks? Can it be a new interesting field to look at? Mostly for the Signal Processing or Physics community.
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We show that the derived approximation rates are optimal (up to log factors) in the class of modReLU networks with weights of moderate growth. Keywords. complex ...
A Structural Optimization Algorithm for Complex-Valued Neural Networks
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A pruning algorithm with group lasso regularization is proposed in this paper, where both the superfluous hidden and input neurons can be efficiently removed.
Aug 14, 2024 · The purpose of this paper is to show how complex-valued neural networks (CVNNs) can be efficiently designed by using a novel algorithm based on ...