Comparing Analog and Digital Processing for Ultra Low-Power Embedded Artificial Intelligence-Reference-Cited by-同舟云学术

Comparing Analog and Digital Processing for Ultra Low-Power Embedded Artificial Intelligence

Published:2022-11-24 Issue: Volume: Page:
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Container-title:2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)
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Author:

Marzetti Sebastian¹,Gies Valentin¹,Barchasz Valentin¹,Barthelemy Herve¹,Glotin Herve²

Affiliation:

1. Aix Marseille Université, Université de Toulon, CNRS, IM2NP,UMR,France,7334

2. Université de Toulon, Aix Marseille Univ, CNRS, LIS, DYNI,Marseille,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9975794/9975848/09975931.pdf?arnumber=9975931

Reference19 articles.

1. TelosW: Enabling ultra-low power wake-on sensor network

2. Analog ultra low-power acoustic wakeup system based on frequency detection;fourniol;2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS),2018

3. A Low Power Wake-Up Circuitry Based on Dynamic Time Warping for Body Sensor Networks

4. Low-Power Wake-Up System based on Frequency Analysis for Environmental Internet of Things

5. Applications of an Ultra Low-Power Analog Wake-up Detector for Environmental IoT Networks and Military Smart Dust

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