Table 1.

Comparison of the classification accuracy of the proposed SOM-SNN framework against other ANNs and SNN-based frameworks on the RWCP dataset.

Model	Accuracy (%)
MLP	99.45
CNN	99.85
RNN	95.35
LSTM	98.40
SOM-RNN	97.20
SOM-LSTM	98.15
LSF-SNN (Dennis et al., 2013)	98.50
LTF-SNN (Xiao et al., 2017)	97.50
SOM-SNN (ReSuMe)	97.00
SOM-SNN (Maximum-Margin Tempotron)	99.60

The average results over 10 experimental runs with random weight initialization are reported.