Results 151 to 160 of about 134,557 (305)

FDD Channel Estimation via Covariance Estimation in Wideband Massive MIMO Systems. [PDF]

Sensors (Basel), 2020
González-Coma JP, Suárez-Casal P, Castro PM, Castedo L.   +3 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Using Covariance Factor in Genetic Parameter Estimation

Veterinary Sciences and Practices, 2022
Ömer ELTAS, Mehmet TOPAL
doaj   +1 more source

A Kinetic–Energetic Bottleneck of Charge‐Transfer Injection Governs Energy Loss in Organic Solar Cells

Advanced Energy Materials, EarlyView.
Kinetic–energetic projection of time‐resolved photoluminescence reveals that charge‐transfer injection acts as a universal bottleneck in organic solar cells. A physics‐constrained Bayesian framework identifies an emergent effective CT injection rate governing the trade‐off between charge generation and nonradiative energy loss.
Rong Wang, Tobias Osterrieder, Atul Shukla, Christos L. Chochos, Vasilis G. Gregoriou, Yakun He, Hua Tang, Julian Matthias Haffner‐Schirmer, Karen Forberich, Ning Li, Thomas Heumueller, Frédéric Laquai, Jens Hauch, Safa Shoaee, Dieter Neher, Larry Lüer, Christoph J. Brabec   +16 more
wiley   +1 more source

Bootstrapping heteroskedasticity consistent covariance matrix estimator [PDF]

Recent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods can be successfully used to estimate a heteroskedasticity robust covariance matrix estimator. In this paper, we show that the wild bootstrap estimator can be calculated directly,
Emmanuel Flachaire
core  

Joint State and Noise Covariance Estimation

Robotics: Science and Systems XXI
This paper tackles the problem of jointly estimating the noise covariance matrix alongside states (parameters such as poses and points) from measurements corrupted by Gaussian noise and, if available, prior information. In such settings, the noise covariance matrix determines the weights assigned to individual measurements in the least squares problem.
Khosoussi, Kasra, Shames, Iman
openaire   +4 more sources

Labeling Quality or Quantity? The Differential Impact of Geographical Indications on Export Performance in Turkish Agri‐Food Products

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This study investigates the impact of geographical indication (GI) certification on the export performance of Turkish agri‐food products by analyzing both trade volume and unit value dynamics. Drawing on monthly data from 2000 to 2024 across 22 GI‐certified products, the research employs product‐level regressions, fixed‐effects panel models ...
Ihlas Sovbetov, Muge Burcu Ozdemir
wiley   +1 more source

Robust Kalman Filter with Recursive Measurement Noise Covariance Estimation Against Measurement Faults

International Journal of Prognostics and Health Management
A new innovation-based recursive measurement noise covariance estimation method is proposed. The presented algorithm is used for Kalman filter tuning, as a result, the robust Kalman filter (RKF) against measurement malfunctions is derived.
Chingiz Hajiyev
doaj   +1 more source

Do outgrower schemes enhance technology adoption and productivity? Evidence from maize farmers in Northern Ghana

Agribusiness, EarlyView.
Abstract Nucleus outgrower schemes are contractual arrangements where well‐resourced large‐scale farmers (nucleus farmers) are empowered by development support agencies to take charge of smallholder farmers, by providing them with market access and the necessary training on agronomic practices and farm inputs for production.
Dominic Tasila Konja, Awudu Abdulai
wiley   +1 more source

A singular spectrum analysis: problems and solutions

St. Petersburg Polytechnical University Journal: Physics and Mathematics
The paper has examined various aspects of the singular spectrum analysis (SSA) method. The original purpose of the method is to optimize harmonic (spectral) analysis of time series.
Pichugin Yury, Pichugina Nika
doaj   +1 more source