Abstract

The flexible electronics has been deemed to be a promising approach to the wearable electronic systems. However, the mismatching between the existing flexible deices and the conventional computing paradigm results an impasse in this field. In this work, a new way to access to this goal is proposed by combining flexible devices and the neuromorphic architecture together. To achieve that, a high-performance flexible artificial synapse is created based on a carefully designed and optimized memristive transistor. The device exhibits high-performance which has near-linear non-volatile resistance change under 10,000 identical pulse signals within the 515% dynamic range, and has the energy consumption as low as 45 fJ per pulse. It also displays multiple synaptic plasticity features, which demonstrates its potential for real-time online learning. Besides, the adaptability by virtue of its three-terminal structure specifically contributes its improved uniformity, repeatability, and reduced power consumption. This work offers a very viable solution for the future wearable computing.

Highlights

  • The flexible electronics has become a very attractive field

  • As a proof-of-concept, the artificial neural network has already achieved a success on software level using the and central processing unit (CPU) and graphics processing unit (GPU) on conventional computers and proved its effectiveness on cognitive computing.[11]

  • A new approach of wearable electronic system was proposed by combining flexible devices and the neuromorphic system

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Summary

Introduction

Tons of flexible devices have been reported during the past decades, with different device structures and materials, working as sensors,[1,2,3] computing blocks,[4] or display units.[5,6] For noncomputing components, the achievements are very satisfactory. Lots of devices step toward practical use, for example, the electronic skins[3,7,8] and the wearable sensors.[1] when it comes to the computing component, the situation is not comforting. There were some demonstrations for flexible circuit[4,9] based on the conventional computing architectures, e.g., von Neumann and Modified Harvard, the functions and performance were very limited and clearly insufficient for processing those numerous less structured[10] information receiving from the environment and the human body. A direct transplant of that way into the flexible computers is hard, the same dilemma still exists because of the unsatisfied flexible device performance

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