Results 201 to 210 of about 76,325 (312)

Learning and Real-time Classification of Hand-written Digits With\n Spiking Neural Networks [PDF]

, 2017
Shruti Kulkarni, John M. Alexiades, Bipin Rajendran   +2 more
openalex   +1 more source

Deep Spiking Neural Networks

, 2018
Neuromorphic Engineering (NE) has led to the development of biologically-inspired computer architectures whose long-term goal is to approach the performance of the human brain in terms of energy efficiency and cognitive capabilities. Although there are a number of neuromorphic platforms available for large-scale Spiking Neural Network (SNN) simulations,
openaire   +1 more source

Dual Bipolar Resistive Switching in Wafer‐Scalable 2D Perovskite Oxide Nanosheets‐Based Memristor

Advanced Science, EarlyView.
A wafer‐scalable memristor based on 2D Sr2Nb3O₁₀ perovskite oxide nanosheets exhibits dual bipolar resistive switching through controllable oxygen ion migration and redox reactions. This single device enables both STDP and anti‐STDP synaptic functions, achieving 86.4% MNIST accuracy in supervised spiking neural networks, offering a compact, energy ...
Sohwi Kim, Chansoo Yoon, Haena Yim, Taeyoon Kim, Hoyoung Suh, Woohyeon Ryu, Gwangtaek Oh, Jihoon Jeon, Kwanyoung Oh, Yeonjoo Jeong, Ji‐Won Choi, Bae Ho Park   +11 more
wiley   +1 more source

Hybrid recurrent with spiking neural network model for enhanced anomaly prediction in IoT networks security. [PDF]

Front Artif Intell
Mustafa M, Eljack Babiker SM, Mustafa YEA.   +2 more
europepmc   +1 more source

H⁺ Exchange‐Driven ppb‐Level and High‐Selective Formaldehyde Detection at Room Temperature for Environmental and Clinical Applications

Advanced Science, EarlyView.
This article presents an innovative room‐temperature formaldehyde sensor based on H⁺ exchange method, achieving ppb‐level detection limit and exceptional selectivity. The study highlights its practical potential for real‐time environmental monitoring and clinical diagnostic applications.
Lubing Cai, Mengyang Pang, Zhaosong Liu, Yanfei Li, Jiani Li, Zhaorui Zhang, Fengshuang Zheng, Chao Li, Ang Zheng, Xuemin Zhang   +9 more
wiley   +1 more source

Emergence of sparse coding, balance and decorrelation from a biologically-grounded spiking neural network model of learning in the primary visual cortex. [PDF]

PLoS Comput Biol
Ruslim MA, Spencer MJ, Hogendoorn H, Meffin H, Lian Y, Burkitt AN.   +5 more
europepmc   +1 more source

Temporal Hierarchy in Spiking Neural Networks

Filippo Moro, Pau Vilimelis Aceituno, Laura Kriener, Melika Payvand   +3 more
openalex   +1 more source

Toward One-Shot Learning in Neuroscience-Inspired Deep Spiking Neural Networks [PDF]

, 2019
Faramarz Faghihi, H. Molhem, Ahmed A. Moustafa   +2 more
openalex   +1 more source

Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries

Advanced Science, EarlyView.
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang, Wenkai Wang, Zhenling Peng, Jianyi Yang   +3 more
wiley   +1 more source

A spiking neural network for active efficient coding. [PDF]

Front Robot AI
Barbier T, Teulière C, Triesch J.
europepmc   +1 more source