Proteinoid-Rhodopsin-Based Spiking Neuron

Name: Proteinoid-Rhodopsin-Based Spiking Neuron
Creator: University of Manchester; University of the West of England
Published: 2024-12-12T00:00:00+08:00

Zenodo2024-12-12 更新2026-04-07 收录

神经形态计算

脉冲神经网络

数据链接：

https://zenodo.org/doi/10.5281/zenodo.14418161 数据链接链接失效反馈

官方服务：

资源简介：

Data of potential vs time for paper ''Proteinoid-Rhodopsin-Based Spiking Neuron''.

提供机构：

University of Manchester; University of the West of England

创建时间：

2024-12-12

Data and code underlying the research of: SRIF-ADC for CIM accelerators

集成电路设计

神经形态计算

This targets neuromorphic and general-purpose arithmetic applications. A scalable and reliable integrate and fire circuit ADC (SRIF-ADC) design for CIM architectures is presented, suitable for stringe

Mendeley Data2024-06-25 更新130

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks

脉冲神经网络

优化算法

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing

NIAID Data Ecosystem40

Data&Code for Resolving the Complexity of Microstructure Evolution Using Spiking Neural Networks

微观结构演化

脉冲神经网络

Microstructure evolution is ubiquitous in nature and important in engineering, often understood through a field-based description.In this work, we decipher its intricate spatiotemporal complexity usin

Figshare2025-01-23 更新20

Table 1_Review of deep learning models with Spiking Neural Networks for modeling and analysis of multimodal neuroimaging data.xlsx

脉冲神经网络

多模态神经影像

Medical imaging has become an essential tool for identifying and treating neurological conditions. Traditional deep learning (DL) models have made tremendous advances in neuroimaging analysis; however

NIAID Data Ecosystem100

Engineering Titanium Dioxide/Titanocene-Polysulfide Interface for Flexible, Optical-Modulated, and Thermal-Tolerant Multilevel Memristor

新型忆阻器

神经形态计算

Multifunctional memristors with a high memory density, low power consumption, flexibility, programmability, and environmental robustness are essential for next-generation memories. In this work, a tit

NIAID Data Ecosystem20

Proteinoid-Rhodopsin-Based Spiking Neuron

资源简介：

相关数据集