Results 81 to 90 of about 9,759 (265)
Selective Range Iterative Adaptive Approach for High-Resolution DOA Estimation
In this paper, the problem of direction-of-arrival (DOA) estimation for a uniform linear array with single-snapshot observations is addressed. Two non-parametric DOA estimators are developed, which can be applied in any azimuth range with one snapshot ...
Yuan Chen +2 more
doaj +1 more source
Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar +10 more
wiley +1 more source
Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation [PDF]
This paper is concerned with the estimation of covariance matrices in the presence of heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that are designed for this context depend upon the choice of a lag truncation parameter and a weighting scheme.
openaire +1 more source
A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren +5 more
wiley +1 more source
Ubiquilin (UBQLN), like many other human proteins, contains both well‐folded and disordered regions. Here, we show that intramolecular interactions between disordered regions and folded domains modulate between open and closed topologies of UBQLN proteins, altering their structure and function.
Jessica K. Niblo +4 more
wiley +1 more source
Optimal estimators in biadditive models and their families
Biadditive regression models are linear models with an additive structure for their covariance matrix. We introduce commutative conditions and derive optimal estimators, namely Best Linear Unbiased Estimators (BLUE) and Best Quadratic Unbiased Estimators
Manuela Oliveira +4 more
doaj +1 more source
Minimax estimators of a covariance matrix
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li +6 more
wiley +1 more source
Shrinking the Variance-Covariance Matrix: Simpler is Better
This study focuses on the estimation of the covariance matrix as an input to portfolio optimization. We compare 12 covariance estimators across four categories – conventional methods, factor models, portfolios of estimators and the shrinkage approach ...
Muhammad Husnain +2 more
doaj
Estimation of a Covariance Matrix Using the Reference Prior
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Ruoyong, Berger, James O.
openaire +2 more sources

