Results 111 to 120 of about 192,869 (306)

Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage

, 2016
We establish large sample approximations for an arbitray number of bilinear forms of the sample variance-covariance matrix of a high-dimensional vector time series using $ \ell_1$-bounded and small $\ell_2$-bounded weighting vectors.
Steland, Ansgar, von Sachs, Rainer
core   +1 more source

An Intelligent Magneto‐Mechanical Platform for Cellular Sensing in 3D Microenvironments

Advanced Science, EarlyView.
This study presents MagMI, a pioneering machine intelligence‐driven magneto‐mechanical sensing platform. It utilizes magneto‐mechanical arrays and machine learning to achieve label‐free, real‐time monitoring and classification of cellular proliferation dynamics within 3D microenvironments.
Yue Quan, Yuxin Wang, Sen Ding, Bingpu Zhou, Yinning Zhou   +4 more
wiley   +1 more source

Comparison of NMC and Ensemble-Based Climatological Background-Error Covariances in an Operational Limited-Area Data Assimilation System

Atmosphere, 2019
The evaluation of several climatological background-error covariance matrix (defined as the B matrix) estimation methods was performed using the ALADIN limited-area modeling data-assimilation system at a 4 km horizontal grid spacing.
Antonio Stanesic, Kristian Horvath, Endi Keresturi   +2 more
doaj   +1 more source

Positive Definite $\ell_1$ Penalized Estimation of Large Covariance Matrices [PDF]

, 2012
The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis.
Ma, Shiqian, Xue, Lingzhou, Zou, Hui
core  

Polarization‐Dependent 3D Holography Generated by Inverse Design Nanoprinting Metasurface

Advanced Science, EarlyView.
A novel polarization‐dependent 3D holography is proposed by introducing polarization as an additional freedom, enabling enhanced depth selectivity and greater control over holographic reconstruction. The efforts perfectly combine the polarization and 3D holography display into ADAM gradient descent algorithm, the application of nanoprinting further ...
Lingxing Xiong, Jintao Gong, Fei Zhang, Wenhao Miao, Qiong He, Dapeng Zhang, Yangjian Cai, Nan Chi   +7 more
wiley   +1 more source

Information Geometry for Covariance Estimation in Heterogeneous Clutter with Total Bregman Divergence

Entropy, 2018
This paper presents a covariance matrix estimation method based on information geometry in a heterogeneous clutter. In particular, the problem of covariance estimation is reformulated as the computation of geometric median for covariance matrices ...
Xiaoqiang Hua, Yongqiang Cheng, Hongqiang Wang, Yuliang Qin   +3 more
doaj   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

Jointly Iterative Adaptive Approach Based Space Time Adaptive Processing Using MIMO Radar

IEEE Access, 2018
To solve the problem of large training samples requirement of space time adaptive processing (STAP), a jointly sparse matrices recovery-based method is proposed for clutter plus noise covariance matrix estimation by exploiting the transmitting waveform ...
Weike Feng, Yiduo Guo, Xingyu He, Hanwei Liu, Jian Gong   +4 more
doaj   +1 more source

Two new algorithms for maximum likelihood estimation of sparse covariance matrices with applications to graphical modeling [PDF]

, 2023
Ghania Fatima, Prabhu Babu, Petre Stoica
openalex   +1 more source

A Statistical Mechanics Model to Decode Tissue Crosstalk During Graft Formation

Advanced Science, EarlyView.
We introduce a statistical mechanics framework to decode the genomic crosstalk governing plant grafting. By integrating evolutionary game theory with transcriptomics, we reconstruct idopNetworks (informative, dynamic, omnidirectional, and personalized networks) that map scion–rootstock interactions.
Ang Dong, Yihan Meng, Stephen Shing‐Toung Yau, Shing‐Tung Yau, Rongling Wu   +4 more
wiley   +1 more source