1. Deep reservoir computing based on self-rectifying memristor synapse for time series prediction.
- Author
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Wang, Rui, Liang, Qi, Wang, Saisai, Cao, Yaxiong, Ma, Xiaohua, Wang, Hong, and Hao, Yue
- Subjects
- *
TIME series analysis , *STANDARD deviations , *FORECASTING - Abstract
Herein, a self-rectifying resistive switching memristor synapse with a Ta/NbOx/Pt structure was demonstrated for deep reservoir computing (RC). The memristor demonstrated stable nonlinear analog switching characteristics, with a rectification ratio of up to 1.6 × 105, good endurance, and high uniformity. Additionally, the memristor exhibited typical short-term plasticity and dynamic synaptic characteristics. Based on these characteristics, a deep memristor RC system was proposed for time series prediction. The system achieved a low normalized root mean square error (NRMSE) of 0.04 in the time series prediction of the Henon map. Even at 90 °C, deep RC retains good predictive power with an NRMSE of only 0.07. This work provides guidance for efficient deep memristive RC networks to handle more complex future temporal tasks. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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