An ultra-compact leaky integrate-and-fire neuron with long and tunable time constant utilizing pseudo resistors for spiking neural networks

Spiking neural networks (SNNs) inspired by biological neurons enable a more realistic mimicry of the human brain. To realize SNNs similar to large-scale biological networks, neuron circuits with high area efficiency are essential. In this paper, we propose a compact leaky integrate-and-fire (LIF) ne...

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Veröffentlicht in:Japanese Journal of Applied Physics 2022-05, Vol.61 (SC), p.SC1051
Hauptverfasser: Chen, Xiangyu, Yajima, Takeaki, Inoue, Isao H., Iizuka, Tetsuya
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Sprache:eng
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Zusammenfassung:Spiking neural networks (SNNs) inspired by biological neurons enable a more realistic mimicry of the human brain. To realize SNNs similar to large-scale biological networks, neuron circuits with high area efficiency are essential. In this paper, we propose a compact leaky integrate-and-fire (LIF) neuron circuit with a long and tunable time constant, which consists of a capacitor and two pseudo resistors (PRs). The prototype chip was fabricated with TSMC 65 nm CMOS technology, and it occupies a die area of 1392 μ m 2 . The fabricated LIF neuron has a power consumption of 6 μ W and a leak time constant of up to 1.2 ms (the resistance of PR is up to 600 MΩ). In addition, the time constants are tunable by changing the bias voltage of PRs. Overall, this proposed neuron circuit facilitates the very-large-scale integration of adaptive SNNs, which is crucial for the implementation of bio-scale brain-inspired computing.
ISSN:0021-4922
1347-4065
DOI:10.35848/1347-4065/ac43e4