The Construction and Approximation of ReLU Neural Network Operators
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 paramet...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Function Spaces |
| Online Access: | http://dx.doi.org/10.1155/2022/1713912 |
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