Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/3322
Title: Towards efficient and adaptive cyber physical spiking neural integrated systems
Authors: Madrena, Jordi
Zapata, Mireya
Fernández, Daniel
Sánchez-Chiva, Josep María
Valle, Juan
Mata-Hernández, Diana
Oltra, Josep
Cosp-Vilella, Jordi
Sato, Shigeo
Issue Date: 2020
Publisher: ICECS 2020 - 27th IEEE International Conference on Electronics, Circuits and Systems, Proceedings. 23 November 2020. 27th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2020. Glasgow. 23 November 2020 through 25 November 2020
Abstract: This work introduces multi-sensor integration combined with an efficient and adaptive Spiking Neural Network (SNN) emulation architecture for local intelligent processing. For this purpose, we propose CMOS-MEMS with on-chip conditioning electronics together with spike processing by means of a real-time bioinspired and model-programmable SIMD multiprocessor. System integration considerations and results in the MEMS and processor developments are provided. © 2020 IEEE.
URI: https://ieeexplore.ieee.org/document/9294982
http://repositorio.uti.edu.ec//handle/123456789/3322
Appears in Collections:Artículos Científicos Indexados

Files in This Item:
There are no files associated with this item.


This item is licensed under a Creative Commons License Creative Commons