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In the present paper, we construct a new type of two-hidden-layer feedforward neural network operators with ReLU activation function. We estimate the rate of approximation by the new operators by using the modulus of continuity of the target function. Furthermore, we analyze features such as parameter sharing and local connectivity in this kind of network structure.
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Chen et al. (2022) studied this question.
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