Frequency Response to AC Input Signal in a Neuristor

The frequency response of a single transistor-based artificial neuron, termed a neuristor, is studied. In contrast to the previously reported spiking properties with direct current (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{\text {DC}}$ </tex-math></inline-formula>) input, the oscillating and spiking properties with alternating current (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{\text {AC}}$ </tex-math></inline-formula>) inputs at different frequencies (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {AC}}$ </tex-math></inline-formula>) are investigated to more realistically mimic neuronal operation in a biological neuron. Without requiring an extra circuit, the neuristor responds to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {AC}}$ </tex-math></inline-formula> lower than the intrinsic threshold frequency (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {th}}$ </tex-math></inline-formula>). Because this <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {th}}$ </tex-math></inline-formula> is modulated by applying gate voltage to the neuristor, its energy efficiency can be further improved.

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Publication Details

Journal
IEEE Transactions on Electron Devices
Published
2024-11-07
DOI
https://doi.org/10.1109/ted.2024.3487085
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.21

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article

Frequency Response to AC Input Signal in a Neuristor

Seong‐Yun Yun, Yang‐Kyu Choi, Ji‐Man Yu, Joon-Ha Son et al.
1 citations
IEEE Transactions on Electron Devices
Advanced Memory and Neural Computing
0.21
article

Frequency Response to AC Input Signal in a Neuristor

Seong‐Yun Yun, Yang‐Kyu Choi, Ji‐Man Yu, Joon-Ha Son, Taegoon Lee, Sangwon Lee
article en
1 citations

Abstract

The frequency response of a single transistor-based artificial neuron, termed a neuristor, is studied. In contrast to the previously reported spiking properties with direct current (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{\text {DC}}$ </tex-math></inline-formula>) input, the oscillating and spiking properties with alternating current (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{\text {AC}}$ </tex-math></inline-formula>) inputs at different frequencies (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {AC}}$ </tex-math></inline-formula>) are investigated to more realistically mimic neuronal operation in a biological neuron. Without requiring an extra circuit, the neuristor responds to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {AC}}$ </tex-math></inline-formula> lower than the intrinsic threshold frequency (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {th}}$ </tex-math></inline-formula>). Because this <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}_{\text {th}}$ </tex-math></inline-formula> is modulated by applying gate voltage to the neuristor, its energy efficiency can be further improved.

IEEE Transactions on Electron DevicesVol. 71(12)
Korea Advanced Institute of Science and Technology (KR)
National Research Foundation of Korea, Samsung
Affordable and clean energy
Openalex Percentile: Top 46%
Advanced Memory and Neural Computing
0.21
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