Results 71 to 80 of about 16,578 (196)

Recursive Feasibility of Nonlinear Stochastic Model Predictive Control With Gaussian Process Dynamics

International Journal of Robust and Nonlinear Control, Volume 36, Issue 9, Page 4957-4970, June 2026.
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf, Andreas Völz, Knut Graichen   +2 more
wiley   +1 more source

Functional models for Nevanlinna families [PDF]

Opuscula Mathematica, 2008
The class of Nevanlinna families consists of \(\mathbb{R}\)-symmetric holomorphic multivalued functions on \(\mathbb{C} \setminus \mathbb{R}\) with maximal dissipative (maximal accumulative) values on \(\mathbb{C}_{+}\) (\(\mathbb{C}_{-}\), respectively)
Jussi Behrndt, Seppo Hassi, Henk de Snoo
doaj  

Symmetric Operators and Reproducing Kernel Hilbert Spaces [PDF]

Complex Analysis and Operator Theory, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

Wheat's war against stripe rust: Integrating host immunity, genomics and breeding for durable resistance

The Plant Genome, Volume 19, Issue 2, June 2026.
Abstract Wheat (Triticum aestivum L.), a foundation of global food security, faces persistent threats from stripe rust caused by Puccinia striiformis f. sp. tritici (Pst). The pathogen thrives in cool and humid environments and regularly causes epidemics that lead to severe yield losses.
Farkhandah Jan, Mukesh Rathore, Dinesh Kumar Saini, Ayushi Singh, Naeela Qureshi, Nikita Aggarwal, Mahpara Bashir, Mehnaz Shakeel, Vikas Gupta, Sundeep Kumar, Rajeev Kumar Varshney, Reyazul Rouf Mir   +11 more
wiley   +1 more source

A benchmarking of genomic selection models for predicting grain‐yield related traits using haplotype‐based and genome‐wide association study‐based markers in rice

The Plant Genome, Volume 19, Issue 2, June 2026.
Abstract Rice (Oryza sativa) is an important staple food, feeding more than half of the global population. A feasible improvement of rice yield is necessary to meet the ever–growing food demands. Genomic selection (GS), as an advanced breeding technique, enables the prediction of phenotypes solely based on genotypic data using a constructed genomic ...
Xiankang Hu, Liu Xian, Guangping Cao, Shuoran Liu, Di Wang, Yanru Che, Weichao Huang, Yanhui Lin, Liqiang He   +8 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  

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Eigenvalue Problem for Discrete Jacobi–Sobolev Orthogonal Polynomials

Mathematics, 2020
In this paper, we consider a discrete Sobolev inner product involving the Jacobi weight with a twofold objective. On the one hand, since the orthonormal polynomials with respect to this inner product are eigenfunctions of a certain differential operator,
Juan F. Mañas-Mañas, Juan J. Moreno-Balcázar, Richard Wellman   +2 more
doaj   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Numerical Simulation of the Kudryashov–Sinelshchikov Equation for Modeling Pressure Waves in Liquids with Gas Bubbles

Mathematics
The Kudryashov–Sinelshchikov equation (KSE) is crucial in modeling pressure waves in liquids containing gas bubbles, capturing both nonlinear wave phenomena and dispersion effects.
Gayatri Das, Bibekananda Sitha, Rajesh Kumar Mohapatra, Predrag Stanimirović, Tzung-Pei Hong   +4 more
doaj   +1 more source