Temporal Learning Using Second-Order Memristors

Utilizing internal dynamic processes in memristors may allow the devices to process temporal data natively. In this letter, we show the ability of second-order memristors to process information in the time domain, and discuss a memristive STDP network that can learn and classify temporal as well as...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on nanotechnology Vol. 16; no. 4; pp. 721 - 723
Main Authors Zidan, Mohammed A., YeonJoo Jeong, Lu, Wei D.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Biological information theory
Biological neural networks
Classification
Electronic devices
feature
Heating systems
Memristors
neural network
Neurons
spike-timing dependent plasticity
Time domain analysis
Timing
Training
Online AccessGet full text

Cover

More Information
Summary:Utilizing internal dynamic processes in memristors may allow the devices to process temporal data natively. In this letter, we show the ability of second-order memristors to process information in the time domain, and discuss a memristive STDP network that can learn and classify temporal as well as classical data patterns.
ISSN:1536-125X
1941-0085
DOI:10.1109/TNANO.2017.2710158