Analog memristive synapse in spiking networks implementing unsupervised learning
Emerging brain-inspired architectures call for devices that can emulate the functionality of biological synapses in order to implement new efficient computational schemes able to solve ill-posed problems. Various devices and solutions are still under investigation and, in this respect, a challenge i...
Main Authors: | Erika Covi, Stefano Brivio, Alexantrou Serb, Themis Prodromakis, Marco Fanciulli, Sabina Spiga |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2016-10-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00482/full |
Similar Items
-
A compound memristive synapse model for statistical learning through STDP in spiking neural networks
by: Johannes eBill, et al.
Published: (2014-12-01) -
Text classification in memristor-based spiking neural networks
by: Jinqi Huang, et al.
Published: (2023-01-01) -
Memristive Spiking Neural Networks Trained with Unsupervised STDP
by: Errui Zhou, et al.
Published: (2018-12-01) -
Non-linear Memristive Synaptic Dynamics for Efficient Unsupervised Learning in Spiking Neural Networks
by: Stefano Brivio, et al.
Published: (2021-02-01) -
Transferable and Flexible Artificial Memristive Synapse Based on WOx Schottky Junction on Arbitrary Substrates
by: Ya Lin, et al.
Published: (2018-12-01)