Hardware-friendly implementation of physical reservoir computing with CMOS-based time-domain analog spiking neurons

Hardware-friendly implementation of physical reservoir computing with CMOS-based time-domain analog spiking neurons

This paper introduces an analog spiking neuron that utilizes time-domain information, i.e. a time interval of two signal transitions and a pulse width, to construct a spiking neural network (SNN) for a hardware-friendly physical reservoir computing (RC) on a complementary metal-oxide-semiconductor p...

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Bibliographic Details
Main Authors: Nanako Kimura, Ckristian Duran, Zolboo Byambadorj, Ryosho Nakane, Tetsuya Iizuka
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Neuromorphic Computing and Engineering
Subjects:
neural network
spiking neurons
leaky integrate-and-fire model
complementary metal-oxide-semiconductor (CMOS)
reservoir computing
hardware
Online Access:https://doi.org/10.1088/2634-4386/addb6d
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