A Heterogeneous Spiking Neural Network for Unsupervised Learning of Spatiotemporal Patterns

A Heterogeneous Spiking Neural Network for Unsupervised Learning of Spatiotemporal Patterns

This paper introduces a heterogeneous spiking neural network (H-SNN) as a novel, feedforward SNN structure capable of learning complex spatiotemporal patterns with spike-timing-dependent plasticity (STDP) based unsupervised training. Within H-SNN, hierarchical spatial and temporal patterns are const...

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Bibliographic Details
Main Authors: Xueyuan She, Saurabh Dash, Daehyun Kim, Saibal Mukhopadhyay
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural network
unsupervised STDP learning
multi-objective prediction
spatiotemporal data processing
neuromorphic computing
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2020.615756/full

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https://www.frontiersin.org/articles/10.3389/fnins.2020.615756/full

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