Time-varying data processing with nonvolatile memristor-based temporal kernel

Recent advances in physical reservoir computing, which is a type of temporal kernel, have made it possible to perform complicated timing-related tasks using a linear classifier. However, the fixed reservoir dynamics in previous studies have limited application fields. In this study, temporal kernel...

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Bibliographic Details
Published in:Nature communications 2021-09, Vol.12 (1), p.5727-5727, Article 5727
Main Authors: Jang, Yoon Ho, Kim, Woohyun, Kim, Jihun, Woo, Kyung Seok, Lee, Hyun Jae, Jeon, Jeong Woo, Shim, Sung Keun, Han, Janguk, Hwang, Cheol Seong
Format: Article
Language:English
Subjects:
639/301/1005/1007
639/925/927/1007
Adaptability
Arrhythmia
Bias
Capacitance
Capacitors
Circuits
Data processing
EKG
Electrocardiography
Humanities and Social Sciences
Information processing
Kernels
Malignancy
Memristors
multidisciplinary
Neural networks
Parameter identification
Science
Science (multidisciplinary)
Semiconductor research
Time constant
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Summary:Recent advances in physical reservoir computing, which is a type of temporal kernel, have made it possible to perform complicated timing-related tasks using a linear classifier. However, the fixed reservoir dynamics in previous studies have limited application fields. In this study, temporal kernel computing was implemented with a physical kernel that consisted of a W/HfO 2 /TiN memristor, a capacitor, and a resistor, in which the kernel dynamics could be arbitrarily controlled by changing the circuit parameters. After the capability of the temporal kernel to identify the static MNIST data was proven, the system was adopted to recognize the sequential data, ultrasound (malignancy of lesions) and electrocardiogram (arrhythmia), that had a significantly different time constant (10 −7 vs. 1 s). The suggested system feasibly performed the tasks by simply varying the capacitance and resistance. These functionalities demonstrate the high adaptability of the present temporal kernel compared to the previous ones. Recently there has been an interest in utilising memristors as physical temporal kernels. Here, Jang et al demonstrate a physical temporal kernel using a memristor combined with a capacitor and resistor, where the additional circuit elements can be varied to allow the system to tackle a diverse range of tasks.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-25925-5