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- W4387183907 abstract "Here we research the multivariate quantitative approximation of Banach space valued continuous multivariate functions on a box or $$mathbb {R}^{N}$$ , $$Nin mathbb {N},$$ by the multivariate normalized, quasi-interpolation, Kantorovich type and quadrature type neural network operators. We investigate also the case of approximation by iterated multilayer neural network operators of the last four types. These approximations are achieved by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its partial derivatives. Our multivariate operators are defined by using a multidimensional density function induced by a q-deformed and parametrized half hyperbolic tangent sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network are with one or multi hidden layers." @default.
- W4387183907 created "2023-09-30" @default.
- W4387183907 creator A5015220542 @default.
- W4387183907 date "2023-01-01" @default.
- W4387183907 modified "2023-09-30" @default.
- W4387183907 title "Banach Space Valued Multivariate Multi Layer Neural Network Approximation Based on q-Deformed and Parametrized Half Hyperbolic Tangent" @default.
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- W4387183907 doi "https://doi.org/10.1007/978-3-031-43021-3_19" @default.
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