Results 81 to 90 of about 15,040 (265)

Kernel estimation of the instantaneous frequency [PDF]

IEEE Transactions on Signal Processing, 1994
We consider kernel estimators of the instantaneous frequency of a slowly evolving sinusoid in white noise. The expected estimation error consists of two terms. The systematic bias error grows as the kernel halfwidth increases while the random error decreases.
openaire   +3 more sources

Oxygen‐Vacancy‐Regulated Crystallization and Ferroelectric Phase Stabilization in Hf0.5Zr0.5O2 Thin Films

Advanced Functional Materials, EarlyView.
Temperature‐resolved in situ grazing‐incidence wide‐angle X‐ray scattering reveals that oxygen vacancies actively regulate crystallization in Hf0.5Zr0.5O2 thin films. By decoupling macroscopic strain from intrinsic phase evolution, a vacancy‐lean environment significantly lowers the activation energy barrier for crystallization.
Hyun Woo Jeong, Jaewook Lee, Junseong Seo, Hyojun Choi, Dong Hee Han, Seungjae Heo, Tae‐Yeol Jeon, Yunseok Kim, Younghwan Lee, Min Hyuk Park   +9 more
wiley   +1 more source

Adaptive Warped Kernel Estimators [PDF]

Scandinavian Journal of Statistics, 2014
AbstractIn this work, we develop a method of adaptive non‐parametric estimation, based on ‘warped’ kernels. The aim is to estimate a real‐valued function s from a sample of random couples (X,Y). We deal with transformed data (Φ(X),Y), with Φ a one‐to‐one function, to build a collection of kernel estimators.
openaire   +3 more sources

Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes

Advanced Functional Materials, EarlyView.
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu, Aditya Raghavan, Utkarsh Pratiush, Ian Mercer, Pochun Hsieh, Albert Suceava, Chih‐Yu Lee, Edgar Dimitrov, Mauricio Terrones, Ichiro Takeuchi, Venkatraman Gopalan, Jon‐Paul Maria, Sergei V. Kalinin   +12 more
wiley   +1 more source

Quantification of Phosphorylated Tau Protein in Alzheimer's Disease Patients’ Fluids With Electrolyte‐Gated Organic Transistor Biosensors

Advanced Healthcare Materials, EarlyView.
Dementia syndrome affects millions of people in the world, and Alzheimer's disease (AD) is the most common cause. We report the detection of the specific biomarker for AD, p‐tau‐181, from physiological to pathological concentrations in cerebrospinal fluid using an electrolyte‐gated organic transistor biosensor.
Marcello Berto, Pamela A. Manco Urbina, Alessandro Paradisi, Matteo Sensi, Najara Iacovino, Chiara Carbone, Roberta Bedin, Marcello Pinti, Fabio Biscarini, Giovanna Zamboni, Carlo A. Bortolotti   +10 more
wiley   +1 more source

Symmetric Positive Semi-Definite Fourier Estimator of Spot Covariance Matrix with High Frequency Data

Risks
This paper proposes a nonparametric estimator of the spot volatility matrix with high-frequency data. Our newly proposed Positive Definite Fourier (PDF) estimator produces symmetric positive semi-definite estimates and is consistent with a suitable ...
Jiro Akahori, Reika Kambara, Nien-Lin Liu, Maria Elvira Mancino, Tommaso Mariotti, Yukie Yasuda   +5 more
doaj   +1 more source

Outlier Detection in Regression Using an Iterated One-Step Approximation to the Huber-Skip Estimator

Econometrics, 2013
In regression we can delete outliers based upon a preliminary estimator and re-estimate the parameters by least squares based upon the retained observations. We study the properties of an iteratively defined sequence of estimators based on this idea.
Søren Johansen, Bent Nielsen
doaj   +1 more source

On Bootstrapping Kernel Spectral Estimates

The Annals of Statistics, 1992
This paper considers the problem of determining the statistical characteristics (such as probability distribution and confidence limits) of a kernel spectral density estimator, by using the bootstrap approach. A simple and natural bootstrapping scheme based on resampling the data periodogram ordinates (appropriately normalized) is introduced.
Franke, J., Hardle, W.
openaire   +2 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source