Spikformer: When Spiking Neural Network Meets Transformer 下载积分: 199 内容提示: 文档格式:PDF | 页数:19 | 浏览次数:3 | 上传日期:2024-11-09 22:25:02 | 文档星级: 阅读了该文档的用户还阅读了这些文档 22 p. PERSE: Personalized 3D Generative Avatars from A Single Portrait 15 p. ...
Kasabov NK (2014) Neucube: a spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Netw 52:62–76 Google Scholar Herz AV, Gollisch T, Machens CK, Jaeger D (2006) Modeling single-neuron dynamics and computations: a balance of detail...
This code is an efficient C++ implementation of a Spiking Neural Network, which was heavily inspired by this work: https://arxiv.org/pdf/1710.10704.pdf. Branches and variations The code contains 6 different branches: master: the revised code that I used for my dissertation, with some ...
Here, we utilized a combination of spiking neural network simulations and analysis of human single-neuron experimental data7 to investigate (1) the mechanisms by which temporally autocorrelated fluctuations in neural activity emerge in spiking neural networks, and (2) whether such fluctuations can accou...
LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition (ijcai.org)www.ijcai.org/Proceedings/2020/0211.pdf Abstract 当前针对目标识别的SNN模型主要是卷积和全连接的架构,只有层与层之间的连接,并没有层内的连接。受到神经科学中横向相互作用的启发,本文提出了LISNN网...
TET-《Temporal Efficient Training Of Spiking Neural Network Via Gradient Re-weighting》 师兄发的论文,中了2022年的ICLR,现在才来做笔记,真是惭愧惭愧~~ 论文传送门:https://arxiv.org/pdf/2202.11946.pdf Abstract SNN由于其事件驱动和节能特性而引起了广泛的研究兴趣,但是由于其激活函数的不可微分性质,很难...
1. Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes [J] . Kasabov Nikola, Capecci Elisa Information Sciences: An International Journal . 2015,第Null期 机译:尖峰神经网络方法用于对脑电时空数据进行认知过程的建模...
Specifically, we use a spiking neural network to classify sleep EEG signals. In addition, we adopt a hybrid macro/micro back propagation algorithm, aiming to overcome the limitations of existing error back propagation methods for spiking neural network. In order to verify the effectiveness of HSNN...
limiting learning to local neural activity and neglecting internal connections between neural responses. Associative memory is a crucial way for the brain to achieve memory, which associates different stimuli through unsupervised learning to establish interconnected network memories. Meanwhile, the human visua...
Spiking neural network. (a) Input data: a circle going in and out of focus, in front of a receptive field (a single pixel). (b) Neural network for focus detection composed of two input neurons,ONandOFF. They directly connect to the output neuron, and also to two blocker neuronsBonand...