Results 161 to 170 of about 1,606 (181)

Reproducing kernel Hilbert space method for optimal interpolation of potential field data

IEEE Transactions on Image Processing, 1998
The RKHS-based optimal image interpolation method, presented by Chen and de Figueiredo (1993), is applied to scattered potential field measurements. The RKHS which admits only interpolants consistent with Laplace's equation is defined and its kernel, derived.
Jonathan S. Maltz, Robert De Mello Koch, Andrew John Willis   +2 more
openaire   +2 more sources

investigating nonlinear fractional systems: reproducing kernel Hilbert space method

Optical and Quantum Electronics, 2023
Deanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia [221412044]
Attia, Nourhane, Akgul, Ali, Alqahtani, Rubayyi T.   +2 more
openaire   +2 more sources

Reproducing Kernel Hilbert Space Methods to Reduce Pulse Compression Sidelobes

2007
Since the development of pulse compression in the mid- 1950's the concept has become an indispensable feature of modern radar systems. A matched filter is used on reception to maximize the signal to noise ratio of the received signal. The actual waveforms that are transmitted are chosen to have an autocorrelation function with a narrow peak at zero ...
Jaco A. Jordaan, Michaël A. van Wyk, Barend J. van Wyk   +2 more
openaire   +1 more source

Global Convergence of Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space

2020 54th Asilomar Conference on Signals, Systems, and Computers, 2020
In supervised learning using kernel methods, we encounter a large-scale finite-sum minimization over a reproducing kernel Hilbert space (RKHS). Often times large-scale finite-sum problems can be solved using efficient variants of Newton’s method, where the Hessian is approximated via subsamples.
Ting-Jui Chang, Shahin Shahrampour
openaire   +1 more source

Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method

Soft Computing, 2015
This paper presents a new method for solving fuzzy differential equations based on the use of the reproducing kernel Hilbert space method under the assumption of strongly generalized differentiability. After some preliminary definitions and results , the paper introduces an overview of the theory of fuzzy differential equations.
Omar Abu Arqub, Mohammed Al-Smadi, Shaher Momani, Tasawar Hayat   +3 more
openaire   +1 more source

Regression models for functional data by reproducing kernel Hilbert spaces methods

Journal of Statistical Planning and Inference, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Solution of Klein-Gordon Equation by a Method of Lines Using Reproducing Kernel Hilbert Space Method

Journal of Partial Differential Equations
Summary: This paper presents a method of lines solution based on the reproducing kernel Hilbert space method to the nonlinear one-dimensional Klein-Gordon equation that arises in many scientific fields areas. Our method uses discretization of the partial derivatives of the space variable to get a system of ODEs in the time variable and then solve the ...
Patel, Kaushal, Patel, Gautam
openaire   +1 more source

A Data Analysis Method Using Orthogonal Transformation in a Reproducing Kernel Hilbert Space

2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023
Lingxiao Qu, Yan Pei 0001, Jianqiang Li 0002   +2 more
openaire   +1 more source

Data-Driven Optimization: A Reproducing Kernel Hilbert Space Approach

Operations Research, 2022
Nihal Koduri, Dimitris J Bertsimas
exaly  

Reproducing kernel Hilbert space method for the numerical solutions of fractional cancer tumor models

Mathematical Methods in the Applied Sciences, 2023
Ali AKGÜL, Djamila Seba, Nourhane Attia   +2 more
exaly