Results 31 to 40 of about 55,665 (307)
A Novel Anti-Jamming Technique for INS/GNSS Integration Based on Black Box Variational Inference
In this paper, a novel anti-jamming technique based on black box variational inference for INS/GNSS integration with time-varying measurement noise covariance matrices is presented. We proved that the time-varying measurement noise is more similar to the
Ping Dong, Jianhua Cheng, Liqiang Liu
doaj +1 more source
Covariance matrix estimation with heterogeneous samples [PDF]
We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp.
Bidon, Stéphanie +2 more
core +1 more source
Nonparametric estimation of covariance functions by model selection [PDF]
We propose a model selection approach for covariance estimation of a stochastic process. Under very general assumptions, observing i.i.d replications of the process at fixed observation points, we construct an estimator of the covariance function by ...
Muniz Alvarez, Lilian +9 more
core +1 more source
Robust covariance estimation for data fusion from multiple sensors [PDF]
This paper addresses the robust estimation of a covariance matrix to express uncertainty when fusing information from multiple sensors. This is a problem of interest in multiple domains and applications, namely, in robotics.
Lazarus, Samuel B. +5 more
core +1 more source
The explicit representation for the limiting spectral moments of sample covariance matrices generated by the periodic autoregressive model (PAR) is established.
Jin Zou, Dong Han
doaj +1 more source
Covariance matrices and valuations
The moment matrix of a function \(f\) of real variables \(x_1,\dots,x_n\) is the matrix, whose \((i,j)\)-th entry is the integral of \(x_i x_j f\) over \(\mathbb{R}^n\). The moment matrix can be regarded as a matrix-valued valuation on the space of functions with finite second moments: recall that a valuation on a space of functions \(L\) is a function
openaire +1 more source
bspcov: An R Package for Bayesian sparse covariance matrix estimation
The bspcov R package provides a Bayesian inference for covariance matrices. The bspcov is developed to aid in research that involves estimating constrained covariance matrices by enabling the use of state-of-the-art Bayesian inference methods.
Kyeongwon Lee +3 more
doaj +1 more source
Spiked sample covariance matrices with possibly multiple bulk components
In this paper, we study the convergent limits and rates of the eigenvalues and eigenvectors for spiked sample covariance matrices whose spectrum can have multiple bulk components.
Ding, Xiucai, Xiucai Ding
core +1 more source
ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang +8 more
wiley +1 more source
Do unbalanced data have a negative effect on LDA? [PDF]
For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class ...
Titterington, D.M., Xue, J.H.
core +1 more source

