MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks

MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks

Spiking Neural Networks (SNNs) are considered more biologically realistic and power-efficient as they imitate the fundamental mechanism of the human brain. Backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, those BP-based...

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Bibliographic Details
Main Authors: Chengting Yu, Yangkai Du, Mufeng Chen, Aili Wang, Gaoang Wang, Erping Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural network (SNN)
leaky integrate-and-fire (LIF) neuron
multiple spike pattern (MSP)
spike frequency adaption (SFA)
state-free synaptic response model (SFSRM)
neuromorphic recognition
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.945037/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.945037/full

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