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Rapid prototyping mixed-signal development kit for tactile neural computing
Intelligent sensor systems are essential for building modern Internet of Things applications. Embedding intelligence within or near sensors provides a strong case for analog neural computing. However, rapid prototyping of analog or mixed signal spiking neural computing is a non-trivial and time-cons...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941318/ https://www.ncbi.nlm.nih.gov/pubmed/36824217 http://dx.doi.org/10.3389/fnins.2023.1118615 |
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author | Mallan, Vasudev S. Gopi, Anitha Reghuvaran, Chithra Radhakrishnan, Aswani A. James, Alex |
author_facet | Mallan, Vasudev S. Gopi, Anitha Reghuvaran, Chithra Radhakrishnan, Aswani A. James, Alex |
author_sort | Mallan, Vasudev S. |
collection | PubMed |
description | Intelligent sensor systems are essential for building modern Internet of Things applications. Embedding intelligence within or near sensors provides a strong case for analog neural computing. However, rapid prototyping of analog or mixed signal spiking neural computing is a non-trivial and time-consuming task. We introduce mixed-mode neural computing arrays for near-sensor-intelligent computing implemented with Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA). The combinations of FPAA and FPGA pipelines ensure rapid prototyping and design optimization before finalizing the on-chip implementations. The proposed approach architecture ensures a scalable neural network testing framework along with sensor integration. The experimental set up of the proposed tactile sensing system in demonstrated. The initial simulations are carried out in SPICE, and the real-time implementation is validated on FPAA and FPGA hardware. |
format | Online Article Text |
id | pubmed-9941318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99413182023-02-22 Rapid prototyping mixed-signal development kit for tactile neural computing Mallan, Vasudev S. Gopi, Anitha Reghuvaran, Chithra Radhakrishnan, Aswani A. James, Alex Front Neurosci Neuroscience Intelligent sensor systems are essential for building modern Internet of Things applications. Embedding intelligence within or near sensors provides a strong case for analog neural computing. However, rapid prototyping of analog or mixed signal spiking neural computing is a non-trivial and time-consuming task. We introduce mixed-mode neural computing arrays for near-sensor-intelligent computing implemented with Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA). The combinations of FPAA and FPGA pipelines ensure rapid prototyping and design optimization before finalizing the on-chip implementations. The proposed approach architecture ensures a scalable neural network testing framework along with sensor integration. The experimental set up of the proposed tactile sensing system in demonstrated. The initial simulations are carried out in SPICE, and the real-time implementation is validated on FPAA and FPGA hardware. Frontiers Media S.A. 2023-02-07 /pmc/articles/PMC9941318/ /pubmed/36824217 http://dx.doi.org/10.3389/fnins.2023.1118615 Text en Copyright © 2023 Mallan, Gopi, Reghuvaran, Radhakrishnan and James. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Mallan, Vasudev S. Gopi, Anitha Reghuvaran, Chithra Radhakrishnan, Aswani A. James, Alex Rapid prototyping mixed-signal development kit for tactile neural computing |
title | Rapid prototyping mixed-signal development kit for tactile neural computing |
title_full | Rapid prototyping mixed-signal development kit for tactile neural computing |
title_fullStr | Rapid prototyping mixed-signal development kit for tactile neural computing |
title_full_unstemmed | Rapid prototyping mixed-signal development kit for tactile neural computing |
title_short | Rapid prototyping mixed-signal development kit for tactile neural computing |
title_sort | rapid prototyping mixed-signal development kit for tactile neural computing |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941318/ https://www.ncbi.nlm.nih.gov/pubmed/36824217 http://dx.doi.org/10.3389/fnins.2023.1118615 |
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