Results 241 to 250 of about 7,675,115 (371)

A Novel Approach to Implementing Artificial Thalamic Neurons with Ferroelectric Transistors

Advanced Functional Materials, EarlyView.
Artificial neurons created using CMOS technology often require a large number of transistors and capacitors. This study introduces an artificial thalamic neuron that employs only five CMOS compatible ferroelectric transistors. The manufactured thalamic neuron demonstrates leaky integrate‐and‐fire‐or‐burst (LIFB) functionalities, featuring self ...
Andreas Grenmyr, Jiayuan Zhang, Jingxuan Sun, Kenta Moto, Stefan Wiefels, Seong‐Ryong Koh, Detlev Grützmacher, Qing‐Tai Zhao   +7 more
wiley   +1 more source

Understanding human amygdala function with artificial neural networks. [PDF]

J Neurosci
Jang G, Kragel PA.
europepmc   +1 more source

Overlapping neural networks for multiple motor engrams. [PDF]

, 1994
A. V. Lukashin, George L. Wilcox, A. P. Georgopoulos   +2 more
openalex   +1 more source

Integration of Perovskite/Low‐Dimensional Material Heterostructures for Optoelectronics and Artificial Visual Systems

Advanced Functional Materials, EarlyView.
Heterojunctions combining halide perovskites with low‐dimensional materials enhance optoelectronic devices by enabling precise charge control and improving efficiency, stability, and speed. These synergies advance flexible electronics, wearable sensors, and neuromorphic computing, mimicking biological vision for real‐time image analysis and intelligent
Yu‐Jin Du, Junjie Yang, Ziyu Lv, Yongbiao Zhai, Zezhuang Yi, Yuhui Xie, Ming‐Lin Zheng, Xiangyu Ma, Guodong Gong, Yan Wang, Ye Zhou, Su‐Ting Han   +11 more
wiley   +1 more source

Coding schemes in neural networks learning classification tasks. [PDF]

Nat Commun
van Meegen A, Sompolinsky H.
europepmc   +1 more source

Introduction to Neural Networks

, 1994
Philip Picton
openalex   +1 more source

Retrieval of pattern sequences at variable speeds in a neural network with delays [PDF]

, 1992
Tom Heskes, Stan Gielen
openalex   +1 more source

Predicting Aggregation Behavior of Nanoparticles in Liquid Crystals via Automated Data‐Driven Workflows

Advanced Functional Materials, EarlyView.
Herein, a comprehensive framework that enabled the optimization of colloidal solubility within a high‐dimensional parameter space and study of reversible assembly processes is developed. This data‐driven workflow integrated innovations including the robotic platform for automated AuNPs functionalization, machine learning for predicting and revealing ...
Yueyang Gao, Niamh Mac Fhionnlaoich, Max Besenhard, Arun Pankajakshan, Federico Galvanin, Stefan Guldin   +5 more
wiley   +1 more source

A review of neural networks for metagenomic binning. [PDF]

Brief Bioinform
Herazo-Álvarez J, Mora M, Cuadros-Orellana S, Vilches-Ponce K, Hernández-García R.   +4 more
europepmc   +1 more source

Artificial neural networks for pattern recognition

, 1994
B. Yegnanarayana
openalex   +2 more sources