Results 111 to 120 of about 3,390,517 (303)

Estimation of a Covariance Matrix Using the Reference Prior

The Annals of Statistics, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Ruoyong, Berger, James O.
openaire   +2 more sources

Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models [PDF]

Estimating a covariance matrix efficiently and discovering its structure are important statistical problems with applications in many fields. This article takes a Bayesian approach to estimate the covariance matrix of Gaussian data.
Christopher K. Carter, Helen Armstrong, Robert Kohn, Kevin K. F. Wong   +3 more
core  

Estimation of Covariance Matrix in Signal Processing When the Noise Covariance Matrix is Arbitrary [PDF]

, 2008
An estimator of the covariance matrix in signal processing is derived when the noise covariance matrix is arbitrary based on the method of maximum likelihood estimation.
Bhandary, Madhusudan, Madhusudan Bhandary   +1 more
core   +1 more source

Coexisting Volatile and Nonvolatile Switching in 3D ALD‐IGZO Vertical RRAM for Fully Hardware‐Based Wide Reservoir Computing

Advanced Science, EarlyView.
A conformal ALD‐IGZO vertical RRAM integrates volatile and nonvolatile switching within a compact 2F architecture. Before forming, tunable volatile dynamics provide fading‐memory reservoir states, while after forming, stable multilevel conductance modulation enables hardware readout.
Seeun Lee, Jaewon Park, Nawoon Kim, Seohyeon Ju, Seong‐Cheol Jang, Hyun‐Suk Kim, Sungjun Kim   +6 more
wiley   +1 more source

Minimax estimators of a covariance matrix

Journal of Multivariate Analysis, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Direction of Arrival Estimation in Low-Grazing Angle: A Partial Spatial-Differencing Approach

IEEE Access, 2017
This paper addresses a partial spatial-differencing (PSD) approach for the direction of arrival estimation in a low-grazing angle (LGA) condition. By dividing the sample covariance matrix into several column subvectors, we first form the corresponding ...
Junpeng Shi, Guoping Hu, Xiaofei Zhang
doaj   +1 more source

Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order [PDF]

This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter.
Wouter J. den Haan, Andrew T. Levin
core  

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

Advanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang, Pengfei Dang, Yuan Tian, Zhengwang He, Wei Gu, Lixue Zhang, Turab Lookman, Yumei Zhou, Dezhen Xue   +8 more
wiley   +1 more source

DOA Estimation Based on Virtual Array Aperture Expansion Using Covariance Fitting Criterion

Remote Sensing
Providing higher precision Direction of Arrival (DOA) estimation has become a hot topic in the field of array signal processing for parameter estimation in recent years.
Teng Ma, Minglei Yang, Hangui Zhu, Yule Zhang, Dingsen Zhou   +4 more
doaj   +1 more source

ROBUST COVARIANCE MATRIX ESTIMATION: "HAC" Estimates with Long Memory/Antipersistence Correction [PDF]

Smoothed nonparametric estimates of the spectral density matrix at zero frequency have been widely used in econometric inference, because they can consistently estimate the covariance matrix of a partial sum of a possibly dependent vector process.
Peter M Robinson
core