Results 311 to 320 of about 2,877,467 (378)

Degree theory for 4‐dimensional asymptotically conical gradient expanding solitons

Communications on Pure and Applied Mathematics, EarlyView.
Abstract We develop a new degree theory for 4‐dimensional, asymptotically conical gradient expanding solitons. Our theory implies the existence of gradient expanding solitons that are asymptotic to any given cone over S3$S^3$ with non‐negative scalar curvature. We also obtain a similar existence result for cones whose link is diffeomorphic to S3/Γ$S^3/\
Richard H. Bamler, Eric Chen
wiley   +1 more source

Addressing Causality and Homogeneity Assumptions in Exposure‐Response Analyses

Clinical Pharmacology &Therapeutics, EarlyView.
Exposure‐response, or pharmacokinetic–pharmacodynamic (PKPD), analyses support many drug development decisions. It is typically applied without assessment of causality and homogeneity, where the latter refers to the assumption that the reason for variability in exposure is unimportant for the impact on response.
Mats O. Karlsson, Divya Brundavanam
wiley   +1 more source

Comparative Analysis of Ledoit's Covariance Matrix and Comparative Adjustment Liability Management (CALM) Model Within the Markowitz Framework

, 2014
Yafei Zhang
openalex   +1 more source

Maximum Likelihood Toeplitz Covariance Matrix Estimation: Is It a Convex Optimization Problem?

Yuri I. Abramovich, Víctor Abramovich, Tanit Pongsiri   +2 more
openalex   +1 more source

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Covariance Matrix Estimation

2016
Covariance matrix estimation allows the adaptation of Gaussian-based mutation operators to local solution space characteristics.
Oliver Kramer
openaire   +2 more sources

An Analysis of Variance of the Pantheon+ Dataset: Systematics in the Covariance Matrix?

Universe, 2022
We investigate the statistics of the available Pantheon+ dataset. Noticing that the χ2 value for the best-fit ΛCDM model to the real data is small, we quantify how significant its smallness is by calculating the distribution of χ2 values for the best-fit
R. Keeley, A. Shafieloo, B. L’Huillier
semanticscholar   +1 more source

Augmented Covariance Matrix Reconstruction for DOA Estimation Using Difference Coarray

IEEE Transactions on Signal Processing, 2021
As is well known, nonuniform linear arrays have significant advantages in array aperture and degrees of freedom over uniform linear arrays. Using their difference coarrays, subspace-based approaches can be utilized to perform underdetermined and high ...
Zhi Zheng, Yixiao Huang, Wen-qin Wang, H. So   +3 more
semanticscholar   +1 more source

DoA Estimation Using Neural Network-Based Covariance Matrix Reconstruction

IEEE Signal Processing Letters, 2021
In this paper, we discuss a new approach to direction of arrival estimation for systems with subarray sampling. We propose to estimate the covariance matrix of the full array from the sample covariance matrices of the subarrays using a neural network ...
Andreas Barthelme, W. Utschick
semanticscholar   +1 more source

Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems

IEEE Wireless Communications Letters, 2020
Multiple signal classification (MUSIC) has been widely applied in wireless communications for direction-of-arrival (DOA) estimation. For massive multiple-input multiple-output (MIMO) systems operating at millimeter-wave bands, hybrid analog-digital ...
Si Li, Yinsheng Liu, Li You, Wenjin Wang, Hongtao Duan, Xu Li   +5 more
semanticscholar   +1 more source

Fast Covariance Matrix Adaptation for Large-Scale Black-Box Optimization

IEEE Transactions on Cybernetics, 2020
Covariance matrix adaptation evolution strategy (CMA-ES) is a successful gradient-free optimization algorithm. Yet, it can hardly scale to handle high-dimensional problems.
Zhenhua Li, Qingfu Zhang, Xi Lin, Hui-Ling Zhen   +3 more
semanticscholar   +1 more source