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Titlebook: Banach Space Valued Neural Network; Ordinary and Fractio George A. Anastassiou Book 2023 The Editor(s) (if applicable) and The Author(s), u

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樓主: arouse
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發(fā)表于 2025-3-23 11:22:51 | 只看該作者
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發(fā)表于 2025-3-23 14:57:31 | 只看該作者
https://doi.org/10.1007/978-3-662-11969-3iate modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the Gudermannian sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer. It follows [.].
13#
發(fā)表于 2025-3-23 18:52:51 | 只看該作者
https://doi.org/10.1007/978-3-662-11969-3te modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the generalized symmetrical sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer.
14#
發(fā)表于 2025-3-24 00:54:36 | 只看該作者
Book 2023 applied sciences like statistics, economics, etc. Therefore, this book is suitable for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries..
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發(fā)表于 2025-3-24 02:57:32 | 只看該作者
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發(fā)表于 2025-3-24 10:26:00 | 只看該作者
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發(fā)表于 2025-3-24 10:46:24 | 只看該作者
Abstract Multivariate Algebraic Function Induced Neural Network Approximations,te modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the algebraic sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer. It follows [.].
18#
發(fā)表于 2025-3-24 18:41:48 | 只看該作者
General Multivariate Arctangent Function Induced Neural Network Approximations, modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the arctangent function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer. It follows [.].
19#
發(fā)表于 2025-3-24 21:37:19 | 只看該作者
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發(fā)表于 2025-3-25 00:18:30 | 只看該作者
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