Results 41 to 50 of about 4,460,603 (181)

Differentiability in reproducing Kernel Hilbert space on the sphere

, 2012
Um espaço de Hilbert de reprodução (EHR) é um espaço de Hilbert de funções construído de maneira específica e única a partir de um núcleo positivo definido.
Jordão, Thaís, Thaís Jordão
core   +1 more source

Cyclicity in Reproducing Kernel Hilbert Spaces of Analytic Functions [PDF]

Computational Methods and Function Theory, 2014
We introduce a large family of reproducing kernel Hilbert spaces $\mathcal{H} \subset \mbox{Hol}(\mathbb{D})$, which include the classical Dirichlet-type spaces $\mathcal{D}_α$, by requiring normalized monomials to form a Riesz basis for $\mathcal{H}$. Then, after precisely evaluating the $n$-th optimal norm and the $n$-th approximant of $f(z)=1-z$, we
Fricain, Emmanuel, Mashreghi, Javad, Seco, Daniel   +2 more
openaire   +4 more sources

Comparative multimodal calibration of patient‐specific atrial fibrillation models: Impact of imaging and electrophysiology data on arrhythmogenic substrate identification

The Journal of Physiology, EarlyView.
Abstract figure legend Comparative multimodal calibration of patient‐specific left atrial (LA) models to identify arrhythmogenic substrates in atrial fibrillation (AF). A, LA models shown in posterior and anterior views, calibrated separately using: late gadolinium enhancement magnetic resonance imaging (LGE‐MRI) image intensity ratio (IIR; blue–red ...
Mahmoud Ehnesh, Haseeb Valli, Ovais A. Jaffery, Sam Coveney, Alexander Zolotarev, Zhong Chen, Wajid Hussain, David G. Jones, Raad Mohiaddin, Tom Wong, Gregory Slabaugh, Steven A. Niederer, Edward Vigmond, Shouvik Haldar, Caroline Roney   +14 more
wiley   +1 more source

Shot‐Based Quantum Encoding: A Data‐Loading Paradigm for Quantum Neural Networks

Advanced Computing, Volume 1, Issue 1, December 2026.
Shot‐based quantum encoding loads classical data without any encoding gates: a learned map turns each datum into a probability vector that dictates how many measurement shots start in each basis state, preparing a mixed state that a shallow variational circuit processes as a quantum perceptron layer.
Basil Kyriacou, Viktoria Patapovich, Maniraman Periyasamy, Alexey Melnikov   +3 more
wiley   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer, Benjamin Wittkop, Andreas Stahl, Olaf Sass, Gregor Welna, Hanna Tietgen, Rod J. Snowdon   +6 more
wiley   +1 more source

Iterative Multistep Reproducing Kernel Hilbert Space Method for Solving Strongly Nonlinear Oscillators [PDF]

, 2014
A new algorithm called multistep reproducing kernel Hilbert space method is represented to solve nonlinear oscillator’s models. The proposed scheme is a modification of the reproducing kernel Hilbert space method, which will increase the intervals of ...
Omar Abu Arqub, Banan Maayah, Samia Bushnaq, Shaher Momani   +3 more
core   +1 more source

Early‐life stage phenomic prediction of field agronomic traits across breeding cycles in intermediate wheatgrass

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Perennial grains represent a promising frontier for sustainable agriculture, but breeding progress is constrained by the accessibility of genotyping and the difficulty of evaluating complex traits expressed for multiple years after establishment across heterogeneous environments.
Zachary N. Harris, Jackson Braley, Eric Cassetta, Jared Crain, Lee DeHaan, David Van Tassel, Allison Miller, Matthew J. Rubin   +7 more
wiley   +1 more source

Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification [PDF]

Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work ...
Alberto Muñoz, Javier González
core  

A reproducing kernel Hilbert space approach to singular local stochastic volatility McKean–Vlasov models

Motivated by the challenges related to the calibration of financial models, we consider the problem of numerically solving a singular McKean–Vlasov equation dXt=σ(t,Xt)XtvtE[vt|Xt]dWt,where Wis a Brownian motion and vis an adapted diffusion process. This
Bayer, Christian, Schoenmakers, John, Schoenmakers, John G. M., Belomestny, Denis, Butkovsky, Oleg   +4 more
core   +1 more source

Frequency‐dependent contraction rates for the Bayesian method to the inverse source problem

Transactions of the London Mathematical Society, Volume 13, Issue 1, December 2026.
Abstract This paper addresses an inverse source problem for acoustic waves in a range of frequencies. Our study has two main goals. First, although the problem is severely ill‐posed with a logarithmic stability estimate, we demonstrate, through careful analysis of the forward map's singular values, that increasing the frequency range enhances stability,
Pu‐Zhao Kow, Jenn‐Nan Wang
wiley   +1 more source