中文翻译版:Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks - 穷酸秀才大草包 - 博客园 (cnblogs.com) 针对sequential and streaming tasks,本文提出了一种自适应脉冲递归神经网络(SRNN),把标准的自适应多时间尺度的脉冲神经元建模为self-recurrent的神经单元,利用代理梯度...
However, most of the Leaky Integrate‐and‐Fire (LIF) neuron models currently used by SNNs based on direct training of backpropagation (BP) do not consider the changes in the recurrent connections and the dynamic strength of neuron connections over time. This study presented the LIF neuron ...
尽管如此,在这些任务中,SNN与当前的深度学习解决方案之间存在显著性能差距。 3 Spiking Recurrent Neural Networks 在此,我们关注由一个或多个循环层组成的SNN,即脉冲循环神经网络(SRNN),如图1a所示。在这些网络中,我们使用两种类型的脉冲神经元之一:LIF神经元(LIF SRNN)和自适应脉冲神经元(Adaptive SRNN)。脉冲神经...
CNN-SRNN代码可在https://github.com/byin-cwi/Efficient-spiking-networks/tree/main/DVS128),深度预处理显著提高了诸如GSC和DVS128数据集36等任务的准确性,其中SRNN的分数超过了参考文献33,35报告的分数。
(2014). Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks. Frontiers in Neural Circuits, *8.* [7] neuron.hirlab.net/ [8] HODGKIN AL, HUXLEY AF. A quantitative description of membrane current and its application ...
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks Article14 October 2021 A solution to the learning dilemma for recurrent networks of spiking neurons ArticleOpen access17 July 2020 Introduction Similar to the brain, neurons in spiking neural networks (SNNs)...
Recurrent spiking neural network with dynamic presynaptic currents based on backpropagation 来自 EBSCO 喜欢 0 阅读量: 144 作者:Z Wang,Y Zhang,H Shi,L Cao,C Yan,G Xu 摘要: In recent years, spiking neural networks (SNNs), which originated from the theoretical basis of neuroscience, have ...
We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We present a hardware efficient methodology to realize ...
Spiking Neural Networks (SNNs) v.s. Recurrent Neural Networks (RNNs) The SNN is NOT anRNN, despite it evolves through time too. For this SNN to be an RNN, I believe it would require some more connections such as from the outputs back into the inputs. In fact, RN...
SNN_文献阅读_Effective and Efficient Computation with Multiple-timescaleSpiking Recurrent Neural Networks Adaptive SRNN 基于多时间尺度脉冲循环神经网络的高效计算(SRNN) 中心思想: 使用替代梯度进行训练,克服SNN中梯度不连续的问题。 在PyTorch中直接使用BPTT进行训练。 结构 本文讨论由一个或者多个递归层组成的SNN—...