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.
Authors
- Seong‐Yun Yun (ORCID: https://orcid.org/0000-0003-4988-1120)
- Yang‐Kyu Choi (ORCID: https://orcid.org/0000-0002-4969-5443)
- Ji‐Man Yu
- Joon-Ha Son
- Taegoon Lee (ORCID: https://orcid.org/0000-0002-8861-1046)
- Sangwon Lee (ORCID: https://orcid.org/0000-0002-6322-8331)
Institutions
- Korea Advanced Institute of Science and Technology (KR)
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
Funders
- National Research Foundation of Korea
- Samsung