25

Spike Timing-Dependent Plasticity Using Memristors and Nano-Crystalline Silicon TFT Memories

Kurtis D. Cantley, Anand Subramaniam,and Eric M. Vogel

CONTENTS

25.1  Introduction

25.2  Device Models

25.3  Synaptic Learning Mechanism

25.3.1  Action Potential Pairs

25.3.2  Spike Triplets

25.3.3  Frequency Dependence

25.4  Discussion

25.5  Applications

25.5.1  Spatio-Temporal Pattern Recognition

25.5.2  Sound Localization

25.5.3  Visual Data Processing

25.6  Conclusions

References

25.1  INTRODUCTION

Interest in the possibility of using memristive devices as synapses in artificial neural circuits was sparked by the demonstration of TiO2 resistive switches by HP Labs in 2008 [1]. A great deal of the resulting research has been centered on implementing ...

Get Nanoelectronic Device Applications Handbook now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.