A method for approximate missing data from data error measured with l norm [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2021 We briefly review some recent work on hypercircle inequality for partially corrupted data when the data error is measured with l norm. The aim of this paper is to present the method for approximate missing data in the use of midpoint algorithm and
Benjawan Rodjanadid, Kannika Khompungson
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A Reproducing Kernel Hilbert Space approach to singular local stochastic volatility McKean-Vlasov models [PDF]
, 2022 Motivated by the challenges related to the calibration of financial models, we consider the problem of numerically solving a singular McKean-Vlasov equation $$ d X_t= \sigma(t,X_t) X_t \frac{\sqrt v_t}{\sqrt {E[v_t|X_t]}}dW_t, $$ where $W$ is a Brownian ...
Bayer, Christian +4 more
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Reproducing Kernel Hilbert Space for Some Non-Gaussian Processes [PDF]
, 1984 Reproducing Kernel Hilbert Space for Some Non-Gaussian ...
Taqqu, M., Czado, C.
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Aveiro method in reproducing kernel Hilbert spaces under complete dictionary [PDF]
Mathematical Methods in the Applied Sciences, 2017 Aveiro method is a sparse representation method in reproducing kernel Hilbert spaces, which gives orthogonal projections in linear combinations of reproducing kernels over uniqueness sets. It, however, suffers from determination of uniqueness sets in the underlying reproducing kernel Hilbert space.
Weixiong Mai, Tao Qian
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Analytic Kramer kernels, Lagrange-type interpolation series and de Branges spaces [PDF]
, 2011 The classical Kramer sampling theorem provides a method for obtaining orthogonal sampling formulas. In particular, when the involved kernel is analytic in the sampling parameter it can be stated in an abstract setting of reproducing kernel Hilbert spaces
Hernández-Medina, Miguel A. +7 more
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Reproducing kernel Hilbert space method for solving fractal fractional differential equations
Results in Physics, 2022 Based on reproducing kernel theory, an analytical approach is considered to construct numerical solutions for some basic fractional ordinary differential equations (FODEs, for short) under fractal fractional derivative with the exponential decay kernel ...
Nourhane Attia +4 more
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A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
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A Novel Method for Solutions of Fourth-Order Fractional Boundary Value Problems
Fractal and Fractional, 2019 In this paper, we find the solutions of fourth order fractional boundary value problems by using the reproducing kernel Hilbert space method. Firstly, the reproducing kernel Hilbert space method is introduced and then the method is applied to this kind ...
Ali Akgül, Esra Karatas Akgül
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Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds [PDF]
2020 59th IEEE Conference on Decision and Control (CDC), 2020 The reproducing kernel Hilbert space (RKHS) embedding method is a recently introduced estimation approach that seeks to identify the unknown or uncertain function in the governing equations of a nonlinear set of ordinary differential equations (ODEs). While the original state estimate evolves in Euclidean space, the function estimate is constructed in ...
Jia Guo 0004 +2 more
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Some error estimates for the reproducing kernel Hilbert spaces method
Journal of Computational and Applied Mathematics, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saeid Abbasbandy, Babak Azarnavid
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