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In<sub>2</sub>O<sub>3</sub> Nanofiber Neuromorphic Transistors for Reservoir Computing

Chuanyu Fu, Hangyuan Cui, Shuo Ke, Yixin Zhu, Xiangjing Wang, Yang Yang, Changjin Wan, Qing Wan

2023IEEE Electron Device Letters11 citationsDOI

Abstract

In this letter, we propose neuromorphic transistors employing indium oxide (In2O3) nanofibers as the channel layers. Basic synaptic function, such as short-term memory can be emulated by one nanofiber neuromorphic transistor. Nonlinear synaptic function and short-term memory characteristic of such neuromorphic transistors are favorable for reservoir computing (RC) system with high energy-efficiency. Ultra-low energy consumption (15 pJ per reservoir state) and ultra-high accuracy (100%) of speech digital recognition are realized based on such nanofiber neuromorphic transistors, proving a great potential of the RC system for intelligent processing tasks.

Topics & Concepts

Neuromorphic engineeringTransistorNanofiberReservoir computingComputer scienceMaterials scienceEnergy consumptionComputer architectureOptoelectronicsElectronic engineeringElectrical engineeringNanotechnologyArtificial neural networkEngineeringArtificial intelligenceRecurrent neural networkVoltageNeural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function
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