Results 71 to 80 of about 910,963 (262)
Principal Component Regression is a method to overcome multicollinearity techniques by combining principal component analysis with regression analysis.
I PUTU EKA IRAWAN +2 more
doaj +1 more source
Magnetic doping of the topological insulator Bi2Te3 with erbium adatoms induces out‐of‐plane magnetism and breaks time‐reversal symmetry, opening a Dirac gap and driving a Fermi surface transition from hexagonal to star‐of‐David geometry. Microscopy, spectroscopy, and magnetic dichroism reveal atomically controlled magnetic interactions that tailor the
Beatriz Muñiz Cano +18 more
wiley +1 more source
Coherent noise source identification in multi channel analysis [PDF]
The evaluation of coherent noise can provide useful information in the study of detectors. The identification of coherent noise sources is also relevant for uncertainty calculations in analyse where several channels are combined.
Frisson, Thibault, Poeschl, Roman
core +1 more source
Direct Laser Writing of Magnetic Micro Actuators With a Stimulus‐Responsive Compliant Hinge
This study presents a versatile modular design strategy for adaptive 3D microactuators. Using two‐photon‐induced C,H insertion reactions within solid polymer layers, chemically distinct hinge and stimulus responsive materials are patterned in one step. The hinge's properties enable tunable motion, mechanical control, and reconfigurable actuation across
Eleonora Galli +4 more
wiley +1 more source
Canonical correlation analysis (CCA) study the linear combinations between a two multivariate set of variable that have the maximum association among these two sets of variables. The main computation of the CCA is depend on the sample mean and covariance
Mufda Jameel Alrawashdeh +3 more
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Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations
In the massive multiple-input multiple-output (MIMO) systems, pilot contamination and signal perturbation are two important issues in the semi-blind channel estimation methods.
Cheng Hu, Hong Wang, Rongfang Song
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Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Inverse problems in covariate data analysis
The fact that Pearson's correlation coefficient and effect size are perspective functions of covariance parameters demonstrates that how covariance is defined is one of the most important issues in data analysis.
Stanley Luck
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This article explores what drives households to adopt solar PV and battery systems in South East Queensland. Using hybrid discrete choice experiments, it reveals distinct adopter profiles and highlights cost, system size, and energy independence as key motivators.
Mohammad Alipour +3 more
wiley +1 more source
The Performance Analysis Based on SAR Sample Covariance Matrix
Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a ...
Esra Erten
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