A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability by Mila Lewerenz, Elias Passerini, Luca Weber, Markus Fischer, Nadia Jimenez Olalla, Raphael Gisler, Alexandros Emboras, Mathieu Luisier, Miklos Csontos, Ueli Koch, Juerg Leuthold

“…The presented results demonstrate the merits of 3T memristors as compact, tunable, and versatile artificial neurons for neuromorphic computing applications.…”
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Optimization of Leaky Integrate-and-Fire Neuron Circuits Based on Nanoporous Graphene Memristors by Kannan Udaya Mohanan, Seyed Mehdi Sattari-Esfahlan, Eou-Sik Cho, Chang-Hyun Kim

Subjects: “…artificial neuron…”
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Low-power artificial neuron networks with enhanced synaptic functionality using dual transistor and dual memristor. by Keerthi Nalliboyina, Sakthivel Ramachandran

“…Artificial neurons with bio-inspired firing patterns have the potential to significantly improve the performance of neural network computing. …”
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Simulating Organic Thin Film Transistors Using Multilayer Perceptron Regression Models to Enable Circuit Design by Laurie E. Calvet, Sami El‐Nakouzi, Zonglong Li, Yerin Kim, Amer Zaibi, Patryk Golec, Ie Mei Bhattacharyya, Yvan Bonnassieux, Lina Kadura, Benjamin Iñiguez

Subjects: “…artificial neuron circuits…”
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Hourly Ozone and PM2.5 Prediction Using Meteorological Data – Alternatives for Cities with Limited Pollutant Information by Felipe Cifuentes, Angel Gálvez, Carlos M. González, Mauricio Orozco-Alzate, Beatriz H. Aristizábal

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ANN Approach to Predict the Flow Stress of CMn (Nb-Ti-V) Micro Alloyed Steel by Abdelhalim ALLAOUI, Abdelmoumene GUEDRI, Lamia DARSOUNI, Abderrazek DARSOUNI

“…Based on experimental stress-deformation data, artificial neuron network (ANN) methods were used to predict flow stress CMn (Nb-Ti-V). …”
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Investigation of ANN Model Containing One Hidden Layer for Predicting Compressive Strength of Concrete with Blast-Furnace Slag and Fly Ash by Hai-Van Thi Mai, Thuy-Anh Nguyen, Hai-Bang Ly, Van Quan Tran

“…In this investigation, an approach using the artificial neuron network (ANN), one of the most powerful machine learning algorithms, is applied to predict the compressive strength of concrete containing BFS and FA. …”
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Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania by Ngong'Ho Bujiku Sende, Snehanshu Saha, Leon Ruganzu, Saibal Kar

“…A variety of supervised machine-learning algorithms such as RBF Kernel in SVM, Linear Kernel in SVM, Polynomial Kernel in SVM, Random Forest, Logistic regression classifier, Decision tree, Gradient Boosting, K-Nearest Neighbours Classifier, Naïve Bayes Classifier, Artificial Neuron Network and Ensemble Learning Model were implemented to predict multidimensional poverty status for each dataset. …”
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Forecast of Chaotic Series in a Horizon Superior to the Inverse of the Maximum Lyapunov Exponent by Miguel Alfaro, Guillermo Fuertes, Manuel Vargas, Juan Sepúlveda, Matias Veloso-Poblete

“…The delay time and the global dimension are employed as parameters in the models of forecast of artificial neuronal networks (ANN) and support vector machine (SVM). …”
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Prosthetic Hand Based on Human Hand Anatomy Controlled by Surface Electromyography and Artificial Neural Network by Larisa Dunai, Isabel Seguí Verdú, Dinu Turcanu, Viorel Bostan

“…These signals were used for feature extraction and classification using an artificial neuronal network. The model converges after 10 sessions, achieving 98% accuracy. …”
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Sliding Mode Real-Time Control of Photovoltaic Systems Using Neural Estimators by J. A. Ramos-Hernanz, O. Barambones, J. M. Lopez-Guede, I. Zamora, P. Eguia, M. Farhat

“…In order to test the designed control system, a photovoltaic module model based on a second artificial neuronal network (ANN) has been obtained from experimental data gathered during 18 months in the Faculty of Engineering Vitoria-Gasteiz (Spain). …”
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Verification of Classification Model and Dendritic Neuron Model Based on Machine Learning by Dongbao Jia, Weixiang Xu, Dengzhi Liu, Zhongxun Xu, Zhaoman Zhong, Xinxin Ban

“…However, traditional artificial neurons still have many problems such as slow and difficult training. …”
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Ultra robust negative differential resistance memristor for hardware neuron circuit implementation by Yifei Pei, Biao Yang, Xumeng Zhang, Hui He, Yong Sun, Jianhui Zhao, Pei Chen, Zhanfeng Wang, Niefeng Sun, Shixiong Liang, Guodong Gu, Qi Liu, Shushen Li, Xiaobing Yan

“…Memristor-based artificial neurons, known for due to their straightforward structure, high energy efficiency, and superior scalability, which enable them to successfully mimic biological neurons with electrical devices. …”
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PlaceField2BVec: A bionic geospatial location encoding method for hierarchical temporal memory model by Zugang Chen, Shaohua Wang, Kai Wu, Guoqing Li, Jing Li, Jian Wang

“…After training, we found that the artificial neurons of HTM formed a place field similar to those of hippocampal neurons in the rat brain and the distribution patterns of the place field from the two kinds of neurons were consistent. …”
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