BPSpike II: A New Backpropagation Learning Algorithm for Spiking Neural Networks

2016 ◽  
pp. 56-65
Author(s):  
Satoshi Matsuda
Keyword(s):  
Neural Networks ◽  
Learning Algorithm ◽  
Spiking Neural Networks ◽  
Backpropagation Learning

Effective Transfer Learning Algorithm in Spiking Neural Networks

2021 ◽  
pp. 1-13
Author(s):  
Qiugang Zhan ◽  
Guisong Liu ◽  
Xiurui Xie ◽  
Guolin Sun ◽  
Huajin Tang
Keyword(s):  
Neural Networks ◽  
Transfer Learning ◽  
Learning Algorithm ◽  
Spiking Neural Networks ◽  
Effective Transfer

scholarly journals Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long-Term Memory Spike Response Model

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xianghong Lin ◽  
Mengwei Zhang ◽  
Xiangwen Wang
Keyword(s):  
Neural Networks ◽  
Supervised Learning ◽  
Learning Algorithm ◽  
Spike Trains ◽  
Spiking Neural Networks ◽  
Long Term Memory ◽  
Response Model ◽  
Spike Response ◽  
Spike Response Model

As a new brain-inspired computational model of artificial neural networks, spiking neural networks transmit and process information via precisely timed spike trains. Constructing efficient learning methods is a significant research field in spiking neural networks. In this paper, we present a supervised learning algorithm for multilayer feedforward spiking neural networks; all neurons can fire multiple spikes in all layers. The feedforward network consists of spiking neurons governed by biologically plausible long-term memory spike response model, in which the effect of earlier spikes on the refractoriness is not neglected to incorporate adaptation effects. The gradient descent method is employed to derive synaptic weight updating rule for learning spike trains. The proposed algorithm is tested and verified on spatiotemporal pattern learning problems, including a set of spike train learning tasks and nonlinear pattern classification problems on four UCI datasets. Simulation results indicate that the proposed algorithm can improve learning accuracy in comparison with other supervised learning algorithms.

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