Memristive Spiking Neural Networks Trained with Unsupervised STDP

Memristive Spiking Neural Networks Trained with Unsupervised STDP

Neuromorphic computing systems are promising alternatives in the fields of pattern recognition, image processing, etc. especially when conventional von Neumann architectures face several bottlenecks. Memristors play vital roles in neuromorphic computing systems and are usually used as synaptic devic...

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Bibliographic Details
Main Authors: Errui Zhou, Liang Fang, Binbin Yang
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Electronics
Subjects:
memristive spiking neural networks (MSNNs)
spike-timing dependent plasticity (STDP)
unsupervised learning
memristor
hardware implementation
Online Access:https://www.mdpi.com/2079-9292/7/12/396

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https://www.mdpi.com/2079-9292/7/12/396

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