Výsledky vyhledávání - "Sylvain Saïghi"

Akademický článek

On-the-Fly Learning With Mixed-Mode Spiking Neural Network and Passive Memristive Array: Application to Neuromorphic Cameras

Autor: Pierre Lewden, Adrien F. Vincent, Jean Tomas, Sylvain Saighi

Publikováno v: IEEE Access, Vol 11, Pp 146103-146121 (2023)

The massive deployment of the Internet of Things (IoT) combined with the need to reduce its impact on global energy consumption calls for the design of intelligent sensors. These sensors must be able to process information in situ to reduce the amoun

Externí odkaz: https://doaj.org/article/0ac96f77a358410c8bfb509999d05ea2

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Akademický článek

A High-Level Methodology to Evaluate and Optimize Digital Architectures Targeting Spike Encoding

Autor: Clemence Gillet, Adrien F. Vincent, Bertrand Le Gal, Sylvain Saighi

Publikováno v: IEEE Access, Vol 11, Pp 120654-120665 (2023)

Spiking Neural Networks (SNNs) are promising candidates for low-power and low-latency embedded artificial intelligence. However, those networks require event-based data produced by neuromorphic sensors which are not widely available, except for a few

Externí odkaz: https://doaj.org/article/0de104579a714d9581c7c8d5c4c6fc0b

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Akademický článek

Learning through ferroelectric domain dynamics in solid-state synapses

Autor: Sören Boyn, Julie Grollier, Gwendal Lecerf, Bin Xu, Nicolas Locatelli, Stéphane Fusil, Stéphanie Girod, Cécile Carrétéro, Karin Garcia, Stéphane Xavier, Jean Tomas, Laurent Bellaiche, Manuel Bibes, Agnès Barthélémy, Sylvain Saïghi, Vincent Garcia

Publikováno v: Nature Communications, Vol 8, Iss 1, Pp 1-7 (2017)

Accurate modelling of memristor dynamics is essential for the development of autonomous learning in artificial neural networks. Through a combined theoretical and experimental study of the polarization switching process in ferroelectric memristors, B

Externí odkaz: https://doaj.org/article/4eca89cea8fb41d595066d4cec248c7a

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Akademický článek

Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization

Autor: Farad Khoyratee, Filippo Grassia, Sylvain Saïghi, Timothée Levi

Publikováno v: Frontiers in Neuroscience, Vol 13 (2019)

Neurological diseases can be studied by performing bio-hybrid experiments using a real-time biomimetic Spiking Neural Network (SNN) platform. The Hodgkin-Huxley model offers a set of equations including biophysical parameters which can serve as a bas

Externí odkaz: https://doaj.org/article/18d3a0f919a04192aeeefe0dfbae5982

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Neuromorphic Technologies, Memristors

Autor: Sylvain Saïghi

Publikováno v: Encyclopedia of Computational Neuroscience ISBN: 9781461473206
Encyclopedia of Computational Neuroscience

The design of analog silicon neurons has now been mastered (Indiveri et al. 2011), lowering computational cost down to a picojoule per action potential. However, considering a ratio of 1,000 synapses to 1 neuron, as observed in biological networks, t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::935c7328317e189459a7bdecb2ffed77
https://doi.org/10.1007/978-1-0716-1006-0_116

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Hardware Spiking Neural Networks: Slow Tasks Resilient Learning with Longer Term-Memory Bits

Autor: Shidoush Siami, Adrien F. Vincent, Charly Meyer, J. Tomas, Sylvain Saïghi, Pierre Lewden

Publikováno v: 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)
2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), Oct 2019, Nara, Japan. pp.1-4, ⟨10.1109/BIOCAS.2019.8918992⟩
BioCAS

International audience; When aiming at efficient and low-power processing of event-based data, hardware implementations of spiking neural networks that co-integrate analog silicon neurons with memristive synaptic crossbar arrays are a promising frame

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7258ac25dc62e5b59f86889f332eb54
https://hal.archives-ouvertes.fr/hal-02487821/document

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Biomimetic Spiking Neural Network (SNN) Systems for ‘In Vitro’ Cells Stimulation

Autor: Sylvain Saïghi, Farad Khoyratee, Teruo Fujii, Kazuyuki Aihara, Stephany Mai Nishikawa, Luo Zhongyue, Timothée Levi, Yoshiho Ikeuchi, Soo Hyeon Kim

Publikováno v: 2019 IEEE International Symposium on Circuits and Systems (ISCAS)
2019 IEEE International Symposium on Circuits and Systems (ISCAS), May 2019, Sapporo, Japan. pp.1-5, ⟨10.1109/ISCAS.2019.8702407⟩
ISCAS

Millions of people are affected by neurological disorders. Brain-Machine Interfaces (BMIs) and neuroprosthesis have been the object of extensive research and may represent a valid treatment for diverse neurological diseases. The realization of neurop

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8e3826088bebdbb813f01803ec776be
https://hal.archives-ouvertes.fr/hal-02484011

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Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization

Autor: Sylvain Saïghi, Farad Khoyratee, Filippo Grassia, Timothée Levi

Publikováno v: Frontiers in Neuroscience, Vol 13 (2019)
Frontiers in Neuroscience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c68a1ea01126b886a1fb96bf5b5b32c
https://www.frontiersin.org/article/10.3389/fnins.2019.00377/full

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Innovative embedded vision systems revolutionise autonomous driving

Autor: Sylvain Saïghi

The long term goal of ULPEC is to develop advanced vision applications with ultra-low power requirements and ultra-low latency. The output of the ULPEC project is a demonstrator connecting a neuromorphic event-based camera to a high speed ultra-low p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::0cab980052988c8b28a570035d1b0fa0
https://zenodo.org/record/3377132

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