Results 71 to 80 of about 3,390,517 (303)
Efficient parallel computation of the estimated covariance matrix [PDF]
2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel, 2010 Computation of a signal's estimated covariance matrix is an important building block in signal processing, e.g., for spectral estimation. Each matrix element is a sum of products of elements in the input matrix taken over a sliding window. Any given product contributes to multiple output elements, thereby complicating parallelization.
Oded Green +3 more
openaire +2 more sources
An Introduction to Shrinkage Estimation of the Covariance Matrix: A Pedagogic Illustration
Spreadsheets in Education, 2011 Shrinkage estimation of the covariance matrix of asset returns was introduced to the finance profession several years ago. Since then, the approach has also received considerable attention in various life science studies, as a remedial measure for ...
Clarence C. Y. Kwan
doaj
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe polarimetric synthetic aperture radar tomography (TomoSAR) technique has proven to be a highly promising cutting-edge microwave remote sensing technique for obtaining forest vertical structure parameters because of its ability in three-dimensional ...
Youjun Wang +7 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye +8 more
wiley +1 more source
Automatic Lag Selection in Covariance Matrix Estimation [PDF]
The Review of Economic Studies, 1994 Summary: We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix. For a given kernel for weighting the autocovariances, we prove that our procedure is asymptotically equivalent to one that is optimal under a mean-squared error ...
Kenneth D. West, Whitney K. Newey
openaire +2 more sources
Advanced Functional Materials, EarlyView.A geometry‐reconfigured additive manufacturing strategy converts planar printed soft materials into soft compact neural probes with integrated hydrogel electrodes and microfluidic channels. The resulting NeuroMAP platform enables scalable multichannel recording, localized chemical delivery, stable in vivo electrophysiological recording, and reduced ...
Hyunjin Lee +15 more
wiley +1 more source
Robust Covariance Matrix Estimation using Random Matrix Theory
, 2023 Covariance matrix estimation plays an important role in multivariate statistics and has found use in a wide range of fields including signal processing, machine learning, and finance. The most commonly used estimator is the sample covariance matrix (SCM).
Deshmukh, Samruddhi +2 more
core +1 more source
Unified Pressure and Field Response Across Distinct Charge‐Order Regimes in Ti‐Doped CsV3Sb5
Advanced Functional Materials, EarlyView.We microscopically investigate the interplay between charge order and superconductivity in a kagome superconductor across regimes of long‐ and short‐range charge order. Hydrostatic‐pressure and magnetic‐field μSR$\mu{\rm SR}$ measurements reveal remarkably similar superconducting and normal‐state time‐reversal‐symmetry‐breaking responses in both ...
P. Kral +12 more
wiley +1 more source
Inertia Estimation Through Covariance Matrix
IEEE Transactions on Power SystemsThis work presents a technique to estimate on-line the inertia of a power system based on ambient measurements. The proposed technique utilizes the covariance matrix of these measurements and solves an optimization problem that fits such measurements to the synchronous machine classical model.
Federico Bizzarri +5 more
openaire +3 more sources
Advanced Materials, EarlyView.ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald +7 more
wiley +1 more source