Results 91 to 100 of about 192,869 (306)

Shrinkage estimation of large covariance matrices: Keep it simple, statistician? [PDF]

Journal of Multivariate Analysis, 2019
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Ledoit, Olivier, Wolf, Michael
openaire   +5 more sources

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen, Renato S. M. Almeida, Stefan Flauder, Guillaume Couégnat, Kamen Tushtev, Jürgen Horvath, Peter Wriggers, Kurosch Rezwan   +7 more
wiley   +1 more source

Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models

Frontiers in Applied Mathematics and Statistics, 2019
High-dimensional data from molecular biology possess an intricate correlation structure that is imposed by the molecular interactions between genes and their products forming various different types of gene networks.
Frank Emmert-Streib, Frank Emmert-Streib, Shailesh Tripathi, Shailesh Tripathi, Matthias Dehmer, Matthias Dehmer, Matthias Dehmer   +6 more
doaj   +1 more source

A Novel Approach to 3D-DOA Estimation of Stationary EM Signals Using Convolutional Neural Networks

Sensors, 2020
This paper proposes a novel three-dimensional direction-of-arrival (3D-DOA) estimation method for electromagnetic (EM) signals using convolutional neural networks (CNN) in a Gaussian or non-Gaussian noise environment.
Dong Chen, Young Hoon Joo
doaj   +1 more source

Robust Estimates of Covariance Matrices in the Large Dimensional Regime [PDF]

IEEE Transactions on Information Theory, 2014
This article studies the limiting behavior of a class of robust population covariance matrix estimators, originally due to Maronna in 1976, in the regime where both the number of available samples and the population size grow large. Using tools from random matrix theory, we prove that, for sample vectors made of independent entries having some moment ...
Couillet, Romain, Pascal, Frédéric, Silverstein, Jack W.   +2 more
openaire   +4 more sources

UniMR: A Plug‐and‐Play Framework of Automated Molecular Recognition for Scanning Tunneling Microscopy

Advanced Science, EarlyView.
UniMR, a training‐free framework for automated molecular recognition in STM images. By integrating adaptive feature selection with CLIP embeddings and Gaussian Mixture Modeling, UniMR achieves robust performance across diverse molecular systems and low‐resolution conditions.
Ziqiang Cao, Lingyin Zhang, Bingzheng Wu, Haonan Chen, Junhao Sun, Linghao Yan, Wenfei Li, Yangyang Wu, Zhifang Wang, Qigang Zhong, Lifeng Chi   +10 more
wiley   +1 more source

Best linear unbiased estimation for varying probability with and without replacement sampling

Special Matrices, 2019
When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated.
Haslett Stephen
doaj   +1 more source

Deformation Prediction of 4D‐Printed Active Composite Structures Based on Data Mining

Advanced Science, EarlyView.
A curvature‐driven sequence point generation (CSPG) algorithm based on data mining is proposed to predict the deformation of double‐layer voxelized composite structures of arbitrary lengths. In addition, the CSPG algorithm is applied to predict the deformation of 2D and 3D structures assembled from beam elements, and its effectiveness is validated ...
Mengtao Wang, Yifan Xu, Zaiyang Liu, Hidemitsu Furukawa, Zhongkui Wang, Ren Xu, Lin Meng   +6 more
wiley   +1 more source

On the Identification of Noise Covariances and Adaptive Kalman Filtering: A New Look at a 50 Year-Old Problem

IEEE Access, 2020
The Kalman filter requires knowledge of the noise statistics; however, the noise covariances are generally unknown. Although this problem has a long history, reliable algorithms for their estimation are scant, and necessary and sufficient conditions for ...
Lingyi Zhang, David Sidoti, Adam Bienkowski, Krishna R. Pattipati, Yaakov Bar-Shalom, David L. Kleinman   +5 more
doaj   +1 more source

Discovery of an Adaptive Neuroimmune Response Driving Itch and Fast Tick Removal with Implications for Preventing Pathogen Transmission

Advanced Science, EarlyView.
Doehl et al. discovered an adaptive neuroimmune mechanism that induces itch in tick‐exposed guinea pigs, enabling rapid tick removal. This itch‐induced tick removal (IITR) is mediated by an adaptive cellular immune response and is independent of IgG, IgE, or TRPV1.
Johannes S. P. Doehl, Tiago D. Serafim, Serena Doh, Charles S. Grugan, Eva Iniguez, Luana Rogerio, Ronja Frigard, Ranadhir Dey, Pedro Cecilio, Xinglong Gu, Pang‐Yen Tseng, Aline da Silva Moreira, Mahnaz Minai, James Oristian, Hans Ackerman, Steven Brooks, Caroline Percopo, Siu‐Ping Ng, Derron A. Alves, Lucas Tirloni, Jennifer M. Anderson, Adriana Marques, Fabiano Oliveira, Shaden Kamhawi, Daniel E. Sonenshine, José M. C. Ribeiro, Mark Hoon, Jesus G. Valenzuela   +27 more
wiley   +1 more source