Multiple general sigmoids based Banach space valued neural network multivariate approximation
DOI10.56754/0719-0646.2503.411zbMath1528.41022OpenAlexW4390144442MaRDI QIDQ6147443
Publication date: 15 January 2024
Published in: Cubo (Temuco) (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.56754/0719-0646.2503.411
multivariate neural network approximationmultivariate modulus of continuityabstract approximation\(L_p\) approximationiterated approximationKantorovich type operatorquadrature type operatorgeneral sigmoid functionsQuasi-interpolation operator
Inequalities in approximation (Bernstein, Jackson, Nikol'ski?-type inequalities) (41A17) Rate of convergence, degree of approximation (41A25) Approximation by positive operators (41A36) Approximation by other special function classes (41A30)
Cites Work
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- Approximation results for neural network operators activated by sigmoidal functions
- Multivariate neural network operators with sigmoidal activation functions
- Intelligent systems. Approximation by artificial neural networks
- Univariate hyperbolic tangent neural network approximation
- Multivariate hyperbolic tangent neural network approximation
- Multivariate sigmoidal neural network approximation
- The approximation operators with sigmoidal functions
- Rate of convergence of some neural network operators to the unit-univariate case
- Intelligent computations: abstract fractional calculus, inequalities, approximations
- Intelligent systems II. Complete approximation by neural network operators
- A logical calculus of the ideas immanent in nervous activity
- General multivariate arctangent function activated neural network approximations
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