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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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Solving Duffing-Van der Pol Oscillator Equations of Fractional Order by an Accurate Technique [PDF]
Journal of Applied and Computational Mechanics, 2021 In this paper, an accurate technique is used to find an approximate solution to the fractional-order Duffing-Van der Pol (DVP, for short) oscillators equation which is reproducing kernel Hilbert space (RKHS, for short ) method. The numerical results show
Nourhane Attia +3 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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Soft and hard classification by reproducing kernel Hilbert space methods [PDF]
Proceedings of the National Academy of Sciences, 2002 Reproducing kernel Hilbert space (RKHS) methods provide a unified context for solving a wide variety of statistical modelling and function estimation problems. We consider two such problems: We are given a training set { y i ,
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Fractal and Fractional, 2020 In this research, obtaining of approximate solution for fractional-order Burgers’ equation will be presented in reproducing kernel Hilbert space (RKHS). Some special reproducing kernel spaces are identified according to inner products and norms.
Onur Saldır +2 more
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Journal of Telecommunications and Information Technology, 2021 Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied.
Rachid Fateh, Anouar Darif, Said Safi
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Mathematical Modelling and Analysis, 2018 Based on the reproducing kernel Hilbert space method, a new approach is proposed to approximate the solution of the Black-Scholes equation with Dirichlet boundary conditions and introduce the reproducing kernel properties in which the initial conditions ...
Mohammadreza Foroutan +2 more
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Adaptive Kernel Learning Kalman Filtering With Application to Model-Free Maneuvering Target Tracking
IEEE Access, 2022 Kernel method is a non-parametric linearization method for system modeling, which uses nonlinear projection from input data space to high-dimensional Hilbert feature space and employs kernel function for hiding the projection operator in a linear learner
Yuankai Li +5 more
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