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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Bibliografski detalji

Glavni autori:	Chengting Yu, Yangkai Du, Mufeng Chen, Aili Wang, Gaoang Wang, Erping Li
Format:	Artigo
Jezik:	Inglês
Izdano:	Frontiers Media S.A. 2022-09-01
Serija:	Frontiers in Neuroscience
Teme:	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 pristup:	https://www.frontiersin.org/articles/10.3389/fnins.2022.945037/full
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