Results 91 to 100 of about 15,040 (265)

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Heuristic Kernel Density Estimator for Modal‑Proximity Data

Shuju Caiji Yu Chuli
Different from the classical probability density estimator construction strategies based on the Parzen window method， we propose a heuristic kernel density estimator （HKDE） based on nearest neighbor error measurement function， to improve the accuracy of ...
HE Yulin, CHEN Chunjia, HUANG Zhexue, LI Junjie, FOURNIER‑VIGER Philippe   +4 more
doaj   +1 more source

Variable Kernel Density Estimation

The Annals of Statistics, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Terrell, George R., Scott, David W.
openaire   +2 more sources

Monolithic 3D‐Integrated All‐Solid Ion‐Gated Carbon Nanotube Transistors With Tunable Ionic Conductance for Multi‐Timescale Reservoir Computing

Advanced Materials, EarlyView.
A dual‐timescale reservoir based on monolithically 3D (M3D)‐integrated CNT solid ion‐gated transistors is demonstrated. Tunable ionic dynamics and pulse‐engineered operation enable linear and symmetric synaptic updates. The M3D‐integrated array achieves robust temporal encoding and accurate classification of moving MNIST sequences, highlighting its ...
Haksoon Jung, Hanbin Cho, Yongwoo Lee, Seunghun Baek, Hyeongjun Kim, Yun Goo Ro, Hyunhyub Ko, Joonki Suh, Yong‐Young Noh, Jimin Kwon   +9 more
wiley   +1 more source

Estimation of nonlinear psychophysical kernels

Journal of Vision, 2004
Reverse correlation techniques have been extensively used in physiology (Marmarelis & Marmarelis 1978; Sakai, Naka, & Korenberg, 1988), allowing characterization of both linear and nonlinear aspects of neuronal processing (e.g., Emerson, Bergen, & Adelson, 1992; Emerson & Citron 1992).
openaire   +2 more sources

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source

Polyphenol‐Inspired Materials for Agricultural Applications

Advanced Materials, EarlyView.
This review outlines the use of polyphenol‐inspired materials for sustainable agriculture, highlighting their molecular design, interfacial assembly, structure–property relationships, and prospects toward precision agriculture, climate resilience, ecosystem protection, and circular bioeconomy strategies.
Haofu Liu, Omid Mazaheri, Zhixing Lin, Tianzheng Wang, Jingqu Chen, Yuang Gu, Xia Liang, Deli Chen, Frank Caruso   +8 more
wiley   +1 more source

Analog Tensor Processing With Carbon Nanotube In‐Memory Matrix Multiplications for Edge Computer Vision Acceleration

Advanced Materials, EarlyView.
This work prototypes a carbon nanotube‐based analog tensor core that performs in‐memory, parallel visual processing. Integrating non‐volatile memories and compact circuits, the core enables high‐speed analog matrix multiplications and can demonstrate accurate three dimensional (3D) spatial transformation and edge detection. With lightweight design, the
Jingfang Pei, Lekai Song, Songwei Liu, Yingyi Wen, Yaoqiang Zhou, Yang Liu, Pengyu Liu, Wenyu Cui, Xin Lu, Teng Ma, Zegao Wang, Guohua Hu   +11 more
wiley   +1 more source

Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data [PDF]

Revista Română de Statistică, 2017
In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya-Watson (Nadarya, 1964; Watson, 1964) type kernel estimator. In this estimation procedure, the censored observations are replaced by synthetic data points
Dursun AYDIN, Ersin YILMAZ
doaj  

Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data

Journal of Probability and Statistics, 2011
The nonparametric estimation for the density and hazard rate functions for right-censored data using the kernel smoothing techniques is considered. The “classical” fixed symmetric kernel type estimator of these functions performs well in the interior ...
T. Bouezmarni, A. El Ghouch, M. Mesfioui
doaj   +1 more source