Results 31 to 40 of about 16,869 (201)
A new method for interpolating in a convex subset of a Hilbert space [PDF]
, 2017 International audienceIn this paper, interpolating curve or surface with linear inequality constraints is considered as a general convex optimization problem in a Reproducing Kernel Hilbert Space.
Bay, Xavier +2 more
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Abstract and Applied Analysis, 2013 We use the reproducing kernel Hilbert space method to solve the fifth-order boundary value problems. The exact solution to the fifth-order boundary value problems is obtained in reproducing kernel space.
Yulan Wang +4 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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Abstract and Applied Analysis, 2013 We investigate the effectiveness of reproducing kernel method (RKM) in solving partial differential equations. We propose a reproducing kernel method for solving the telegraph equation with initial and boundary conditions based on reproducing kernel ...
Mustafa Inc +2 more
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New Numerical Method for Solving Tenth Order Boundary Value Problems
Mathematics, 2018 In this paper, we implement reproducing kernel Hilbert space method to tenth order boundary value problems. These problems are important for mathematicians. Different techniques were applied to get approximate solutions of such problems.
Ali Akgül +3 more
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Reproducing kernel functions for linear tenth-order boundary value problems
ITM Web of Conferences, 2018 Higher order differential equations have always been an onerous problem to investigate for the mathematicians and engineers. Different numerical methods were applied to get numerical approximations of such problems.
Akgül Ali +3 more
doaj +1 more source
Reproducing Kernel Hilbert Space Methods for wide-sense self-similar Processes
The Annals of Applied Probability, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nuzman, Carl J., Poor, H. Vincent
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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 ...
Guo, Jia +2 more
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Advances in Difference Equations, 2021 This paper deals with the generalized Bagley–Torvik equation based on the concept of the Caputo–Fabrizio fractional derivative using a modified reproducing kernel Hilbert space treatment.
Shatha Hasan +5 more
doaj +1 more source
Revisiting Kernelized Locality-Sensitive Hashing for Improved Large-Scale Image Retrieval [PDF]
, 2014 We present a simple but powerful reinterpretation of kernelized locality-sensitive hashing (KLSH), a general and popular method developed in the vision community for performing approximate nearest-neighbor searches in an arbitrary reproducing kernel ...
Jiang, Ke, Kulis, Brian, Que, Qichao
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