Furthermore, an implicit generative model (i.e., a probability model) has been found, allowing to perform probabilistic inference on the basis of well-defined statistical mechanisms, and in this way to draw samples from networks of spiking neurons. The first goal of this work is to implement...
Recurrently connected networks of spiking neurons underlie the astounding information processing capabilities of the brain. Yet in spite of extensive research, how they can learn through synaptic plasticity to carry out complex network computations
Supplementary materials for: A solution to the learning dilemma for recurrent networks of spiking neurons Supplementary Figures Supplementary Tables Supplementary Notes 1 Eligibility traces Results中的“Mathematical basis for e-prop”一节中介绍了资格迹。在这里,我们提供有关资格迹的更多信息。首先,我们讨论作为...
当前的预测误差将反馈到LSNN和对帧进行预处理的脉冲CNN。(c) 使用基于奖励的e-prop学习后,对LSNN进行样本试验。从上到下:随机动作的概率,未来奖励的预测,随机突触的学习动态(任意单位),240个样本LIF神经元中10个和160个样本ALIF神经元中10个的脉冲活动以及位于上方脉冲栅格底部的两个样本神经元的膜电位。(d) 受...
大脑中的递归神经网络(Recurrent Neural Networks,RNNs)为实现Gibbs采样提供了一个可能的结构基础。 循环反馈:递归神经网络中,神经元之间存在循环反馈连接,这些连接允许神经元的活动状态在时间上相互影响。 条件更新:通过递归连接,神经元可以逐步更新其活动状态,这类似于Gibbs采样中逐步更新每个变量的过程。 3. 神经元的...
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 ...
LSTMs and other gated recurrent networks (GRUs) (Chung, Gulcehre, Cho, & Bengio, 2014) are conventional ANNs in the sense that they do not use spiking neurons, but they are also unconventional in the sense that they replace units having recurrent connections with ‘cells’ that contain ...
Ref:The Heidelberg Spiking Data Sets for the Systematic Evaluation of Spiking Neural Networks(Formula. 9) Direct measures.输出神经元的膜电位也可用于分类,因为它代表了输出神经元刺激历史的度量。我们定义了几种方法来解码膜电位历史的结果: 最后一步(last-time-step)膜电位:我们将样本最后一个时间步骤的输出...
Recurrent Spiking SOMArtificial neural networks have been applied successfully in many static systems but present someweaknesses if patterns involve a temporal component. Let's note for example in speech recognition orcontextual information, where different of the time interval, is crucial for ...
An efficient methodology for building the billion-transistors systems on chip of tomorrow is a necessity. Networks on chip promise to be the solution for t... TA Bartic,JY Mignolet,V Nollet,... - International Symposium on System-on-chip 被引量: 153发表: 2003年 Networks-on-Chip based Hi...