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From 1.8V to 0.19V voltage bias on analog spiking neuron in 28nm UTBB FD-SOI technology

Abstract : The emergence of new hardware-oriented algorithms for convolutional neural networks (CNNs) or spiking neural networks (SNNs) used for efficient data interpretation, made neuromorphic computing a very promising solution. SNNs are very attractive due to their particularly low power consumption. This paper presents a comprehensive analysis of an analog spiking neuron designed in 28 nm UTBB FD-SOI CMOS technology from STMicroelectronics. Thick oxide MOS transistors with regular VT are selected to perform a low power design enhanced by using sub-threshold bias. The neuron operation is presented and analyzed through SPICE simulations performed at 0.7 V nominal voltage bias. Several parameters control the shape of the neuron response, such as: the synaptic excitation, the spike duration, and the refractory period. The neuron under study was fabricated and characterized for bias voltages ranging from 1.8 V standard bias to the measured limit of 0.19 V. The full functionality of the analog spiking neuron in FD-SOI is demonstrated.
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https://hal.archives-ouvertes.fr/hal-03001733
Contributor : Laurence Ben Tito <>
Submitted on : Thursday, November 12, 2020 - 4:21:51 PM
Last modification on : Thursday, March 18, 2021 - 3:31:17 AM
Long-term archiving on: : Saturday, February 13, 2021 - 8:02:06 PM

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Distributed under a Creative Commons Attribution - NonCommercial 4.0 International License

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  • HAL Id : hal-03001733, version 1

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CEA | UGA | IRIG | CNRS | CEA-GRE | TIMA | MIAI

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V. Cinçon, Elena Ioana Vatajelu, Lorena Anghel, Philippe Galy. From 1.8V to 0.19V voltage bias on analog spiking neuron in 28nm UTBB FD-SOI technology. EUROSOI-ULIS 2020, Sep 2020, Caen, France. ⟨hal-03001733⟩

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