Results 111 to 120 of about 534,560 (282)

Masked Toeplitz covariance estimation

, 2017
The problem of estimating the covariance matrix $ $ of a $p$-variate distribution based on its $n$ observations arises in many data analysis contexts. While for $n>p$, the classical sample covariance matrix $\hat _n$ is a good estimator for $ $, it fails in the high-dimensional setting when $n\ll p$.
Kabanava, Maryia, Rauhut, Holger
openaire   +2 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

Estimating covariance matrices II

Journal of Multivariate Analysis, 1991
AbstractLet S1 and S2 be two independent p × p Wishart matrices with S1 ∼ Wp(Σ1, n1) and S2 ∼ Wp(Σ2, n2). We wish to estimate ζ = Σ2Σ1−1 under the loss function L1 = tr(ζ − ζ)′ Σ2−1(ζ − ζ) Σ1tr ζ. By extending the techniques of Berger, Haff, and Stein for the one sample problem, alternative estimators to the usual estimators for ζ are obtained. However,
openaire   +1 more source

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

Advanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

Joint DOD and DOA Estimation for Bistatic MIMO Radar: A Covariance Trilinear Decomposition Perspective

IEEE Access, 2019
The covariance methods exert an effect on spatially colored (correlated) noise elimination during direction finding in multiple-input multiple-output (MIMO) radar.
Fangqing Wen, Zijing Zhang, Gong Zhang
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Sparse covariance estimation in heterogeneous samples

Electronic Journal of Statistics, 2011
Standard Gaussian graphical models (GGMs) implicitly assume that the conditional independence among variables is common to all observations in the sample. However, in practice, observations are usually collected form heterogeneous populations where such assumption is not satisfied, leading in turn to nonlinear relationships among variables.
Rodríguez, Abel, Lenkoski, Alex, Dobra, Adrian   +2 more
openaire   +4 more sources

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

Advanced Science, EarlyView.
Itch‐induced tick removal (IITR): An acquired neuroimmune mechanism, itch‐induced tick removal, develops after repeated tick exposure, mobilizing T cells and macrophages at the tick bite site to trigger a rapid scratching response that facilitates timely tick removal within a critical window that precedes the transmission of many tick‐borne pathogens ...
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

High‐Dimensional Covariance Estimation From a Small Number of Samples

Journal of Advances in Modeling Earth Systems
We synthesize knowledge from numerical weather prediction, inverse theory, and statistics to address the problem of estimating a high‐dimensional covariance matrix from a small number of samples.
David Vishny, Matthias Morzfeld, Kyle Gwirtz, Eviatar Bach, Oliver R. A. Dunbar, Daniel Hodyss   +5 more
doaj   +1 more source

Cognitive Trajectories from Preclinical Alzheimer's Disease to Dementia

Advanced Science, EarlyView.
A continuous, multi‐domain characterization of cognitive decline across the Alzheimer's disease spectrum identifies when individual cognitive measures become abnormal. Episodic memory declines first, followed by executive function, language, processing speed, and visuospatial abilities, supporting improved clinical interpretation and optimized endpoint
Fredrik Öhman, Lars Lau Raket, Michael Schöll, for the Alzheimer's Disease Neuroimaging Initiative†   +3 more
wiley   +1 more source