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Tunable superconducting neurons for networks based on radial basis functions [PDF]
Beilstein Journal of Nanotechnology, 2022 The hardware implementation of signal microprocessors based on superconducting technologies seems relevant for a number of niche tasks where performance and energy efficiency are critically important.
Andrey E. Schegolev +6 more
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A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions [PDF]
The Scientific World Journal, 2014 Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this
Guang Pan +3 more
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An alternative method for phase-unwrapping of interferometric data [PDF]
Journal of the European Optical Society-Rapid Publications, 2014 In this paper we present a novel algorithm for phase unwrapping where only a subset of data from the wrapped phase map is used to reconstruct the unwrapped phase map as a linear combination of radial basis functions (RBF’s).
de la Rosa-Miranda E. +9 more
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Meshless Computational Strategy for Higher Order Strain Gradient Plate Models
Mathematical and Computational Applications, 2022 The present research focuses on the use of a meshless method for the solution of nanoplates by considering strain gradient thin plate theory. Unlike the most common finite element method, meshless methods do not rely on a domain decomposition.
Francesco Fabbrocino +4 more
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Extended Hermite Radial Basis Functions for Sparse Contours Interpolation
IEEE Access, 2020 In this paper, we present an extended Hermite radial basis functions interpolant for surface reconstruction of sparse contours that allows for shape control with interactive constraints.
Deyun Zhong, Liguan Wang, Lin Bi
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Fluids, 2022 Numerical optimization procedures are one of the most powerful approaches with which to support design processes. Their implementation, nevertheless, involves several conceptual and practical complexities.
Ubaldo Cella +4 more
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Curvature based characterization of radial basis functions: application to interpolation
Mathematical Modelling and Analysis, 2023 Choosing the scale or shape parameter of radial basis functions (RBFs) is a well-documented but still an open problem in kernel-based methods. It is common to tune it according to the applications, and it plays a crucial role both for the accuracy and ...
Mohammad Heidari +2 more
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Performance of Multilayer Perceptron Neural Network Models and Radial-Based Functions in Estimation of Sugar-cane Crop Yield [PDF]
Journal of Agricultural Science and Sustainable Production, 2020 Background and objective: According to the high importance of sustainable crop production in the agro-industry units, intelligent systems such as artificial neural networks should be used to manage farm units.Therefore, the main purpose of this study was
Sina Sharifi +2 more
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Scaling of radial basis functions
IMA Journal of Numerical Analysis, 2023 Abstract This paper studies the influence of scaling on the behavior of radial basis function interpolation. It focuses on certain central aspects, but does not try to be exhaustive. The most important questions are: How does the error of a kernel-based interpolant vary with the scale of the kernel chosen?
Larsson, Elisabeth, Schaback, Robert
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A Fast Solution for the Generalized Radial Basis Functions Interpolant
IEEE Access, 2020 In this paper, we propose a fast solution method of the generalized radial basis functions interpolant for global interpolation. The method can be used to efficiently interpolate large numbers of geometry constraints for implicit surface reconstruction ...
Deyun Zhong, Liguan Wang, Lin Bi
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