Results 91 to 100 of about 120,097 (295)

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

Advanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon, Soeun Park, Yeong Kwon Kim, Juhwan Baek, Ki Han Kim, Seongil Yun, Hyeonchang Son, Jeongeun Choi, Byung Chul Jang, Dong‐Ho Kang   +9 more
wiley   +1 more source

Ensemble Estimation of Information Divergence †

Entropy, 2018
Recent work has focused on the problem of nonparametric estimation of information divergence functionals between two continuous random variables. Many existing approaches require either restrictive assumptions about the density support set or difficult ...
Kevin R. Moon, Kumar Sricharan, Kristjan Greenewald, Alfred O. Hero   +3 more
doaj   +1 more source

When, Where and How to Perform Efficiency Estimation [PDF]

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson ...
Badunenko, Oleg, Henderson, Daniel J., Kumbhakar, Subal C.   +2 more
core   +3 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Nonparametric Density Estimation for Positive Time Series [PDF]

The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions have been put forward to solve this boundary problem. In this paper we propose
Jeroen V.K. Rombouts, Taoufik Bouezmarni
core  

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Mesoporous Carbon Thin Films with Large Mesopores as Model Material for Electrochemical Applications

Advanced Functional Materials, EarlyView.
Mesoporous carbon thin films possessing 70 nm mesopores are prepared on titanium substrates by soft templating of resol resins with a self‐synthesized poly(ethylene oxide)‐block‐poly(hexyl acrylate) block copolymer. A strategy to avoid corrosion of the metal substrate is presented, and the films are extensively characterized in terms of morphology ...
Lysander Q. Wagner, Joshua Schober, Pascal Dippell, Chantal Glatthaar, Smail Mekhilef, David Schäfer, Hannes Hergert, Marcus Rohnke, Matthias T. Elm, Bernd M. Smarsly   +9 more
wiley   +1 more source

Evaluation of the Performance of Kernel Non-parametric Regression and Ordinary Least Squares Regression

JOIV: International Journal on Informatics Visualization
Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors ...
Amjed Mohammed Sadek, Lekaa Ali Mohammed
doaj   +1 more source

On Tail Index Estimation for Dependent, Heterogenous Data [PDF]

In this paper we analyze the asymptotic properties of the popular distribution tail index estimator by B. Hill (1975) for possibly heavy- tailed, heterogenous, dependent processes.
Jonathan B. Hill
core  

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