^Ghosh-Dastidar, Samanwoy, and Hojjat Adeli. "Spiking neural networks." International journal of neural systems 19.04 (2009): 295-308. ^Bohte, Sander M., Joost N. Kok, and Johannes A. La Poutré. "SpikeProp: backpropagation for networks of spiking neurons." ESANN. Vol. 48. 2000. ^Flo...
除了对计算神经科学的这些影响之外,我们发现RSNN可以通过非常节能的稀疏发放活动获得强大的计算和学习能力,这为基于脉冲的计算硬件通过非发放提供了新的应用范例。 Supplementary information for: Long short-term memory and learning-to-learn in networks of spiking neurons 我们在本补充文件中提供了有关正文的模型和...
τ是膜电位时间常数。 原文称这里的模型是SRM,由于SRM是用的动态阈值,上面的式子看上去更像是连续形式的LIF模型。 后突触膜电位计算如下: xj(t)=ΣiΣkwijkyik(t) 这里wijk是与第k个延时突触终端相关联的权重值,把神经元j第一次脉冲发射的时间定义为tj。 这个算法的目标在于学习一系列的脉冲目标发射时间,记...
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...
NetworksofSpikingNeurons:TheThirdGenerationof NeuralNetworkModels WOLFGANGMAASS InstituteforTheoreticalComputerScience,TechnischeUniversit~itGraz (Received27March1996;accepted10November1996) Abstract--Thecomputationalpowerofformalmodelsfornetworksofspikingneuronsiscomparedwiththatofother neuralnetworkmodelsbasedonMcCullochPi...
We anticipate our results will be an important tool in investigating how large networks of spiking neurons self-organize in time to process and encode information in the brain.doi:10.1103/PhysRevX.5.021028Montbrió, ErnestPazó, DiegoRoxin, Alex...
[10] Bohte S M, Kok J N, La Poutre H. Error-backpropagation in temporally encoded networks of spiking neurons[J]. Neurocomputing, 2002, 48(1): 17-37. [11] Ghosh-Dastidar S, Adeli H. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy ...
Here, the silicon neurons operate in real-time, and the speed of the network is independent of the number of neurons or their coupling. However, analog circuits provide only a good qualitative approximation to the exact performance of simulated neurons. Moreover, the design of special-purpose ...
A solution to the learning dilemma for recurrent networks of spiking neurons,郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布!NATURECOMMUNICATIONS,no.1(2020):3625-21Abstract循环连接的脉冲神经元网络是大脑惊人的信息处理能力的基础。然而,尽管进
Modelling and theoretical investigation of learning capabilities of models for neural networks of the brain, in particular of networks of spiking neurons, has focused on learning via synaptic plasticity, such as spike-timing-dependent plasticity (STDP). But experimental data suggest that synaptic plastic...