Rethinking the Role of Normalization and Residual Blocks for Spiking Neural Networks

Rethinking the Role of Normalization and Residual Blocks for Spiking Neural Networks

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Biologically inspired spiking neural networks (SNNs) are widely used to realize ultralow-power energy consumption. However, deep SNNs are not easy to train due to the excessive firing of spiking neurons in the hidden layers. To tackle this problem, we propose a novel but simple normalization techniq...

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Bibliographic Details
Main Authors: Ikegawa, S.-I (Author), Natori, N. (Author), Saiin, R. (Author), Sawada, Y. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Biologically-inspired
Biomimetics
Chemical activation
Energy utilization
Energy-consumption
Neural networks
Neural-networks
Normalisation
normalization
Post-synaptic potentials
Power energy
Pre-activation residual block
pre-activation residual blocks
Simple++
Spiking neural network
spiking neural networks
Ultra-low power
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