Zobrazeno 1 - 10
of 103
pro vyhledávání: '"Elishai Ezra"'
Autor:
Elishai Ezra Tsur, Odelia Elkana
Publikováno v:
Robotics, Vol 13, Iss 3, p 49 (2024)
The landscape of neurorehabilitation is undergoing a profound transformation with the integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing need for advancements in pediatric neurorehabilitation and underscor
Externí odkaz:
https://doaj.org/article/4860ccf2ba274dfa9c6adf5406a41020
Autor:
Raz Halaly, Elishai Ezra Tsur
Publikováno v:
Frontiers in Neurorobotics, Vol 17 (2023)
Autonomous driving is one of the hallmarks of artificial intelligence. Neuromorphic (brain-inspired) control is posed to significantly contribute to autonomous behavior by leveraging spiking neural networks-based energy-efficient computational framew
Externí odkaz:
https://doaj.org/article/af744130cfcc4627af80be8742acdcb0
Autor:
Raz Halaly, Elishai Ezra Tsur
Publikováno v:
Neuromorphic Computing and Engineering, Vol 4, Iss 2, p 024006 (2024)
Model predictive control (MPC) is a prominent control paradigm providing accurate state prediction and subsequent control actions for intricate dynamical systems with applications ranging from autonomous driving to star tracking. However, there is an
Externí odkaz:
https://doaj.org/article/2497f90eb8524cf9a5a881b45dc7506c
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 10, p e1010648 (2022)
Biologically plausible computational modeling of visual perception has the potential to link high-level visual experiences to their underlying neurons' spiking dynamic. In this work, we propose a neuromorphic (brain-inspired) Spiking Neural Network (
Externí odkaz:
https://doaj.org/article/309f295c342a4640a5b5dfe03fddb10a
Autor:
Michael Ehrlich, Yuval Zaidel, Patrice L. Weiss, Arie Melamed Yekel, Naomi Gefen, Lazar Supic, Elishai Ezra Tsur
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Wheelchair-mounted robotic arms support people with upper extremity disabilities with various activities of daily living (ADL). However, the associated cost and the power consumption of responsive and adaptive assistive robotic arms contribute to the
Externí odkaz:
https://doaj.org/article/b8c59fec28cd47eaabbbef5d3bda953e
Publikováno v:
BMC Neuroscience, Vol 21, Iss 1, Pp 1-9 (2020)
Abstract Background Retinal circuitry provides a fundamental window to neural networks, featuring widely investigated visual phenomena ranging from direction selectivity to fast detection of approaching motion. As the divide between experimental and
Externí odkaz:
https://doaj.org/article/6383bd2aebb44613abd328cc1da4e2ea
Autor:
Shoham Jacobsen, Oded Meiron, David Yoel Salomon, Nir Kraizler, Hagai Factor, Efraim Jaul, Elishai Ezra Tsur
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 8, Pp 1-8 (2020)
Background: EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been
Externí odkaz:
https://doaj.org/article/5802484c28584a9f938f0574ae4f3f9e
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 12, p e1009754 (2021)
Retinal direction-selectivity originates in starburst amacrine cells (SACs), which display a centrifugal preference, responding with greater depolarization to a stimulus expanding from soma to dendrites than to a collapsing stimulus. Various mechanis
Externí odkaz:
https://doaj.org/article/8926ab21d0b24aa9a129ed80dfcd0f93
Publikováno v:
Frontiers in Neurorobotics, Vol 15 (2021)
Neuromorphic implementation of robotic control has been shown to outperform conventional control paradigms in terms of robustness to perturbations and adaptation to varying conditions. Two main ingredients of robotics are inverse kinematic and Propor
Externí odkaz:
https://doaj.org/article/feba4b2ad7c84cbbac210af8dd8655df
Autor:
Avi Hazan, Elishai Ezra Tsur
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Brain-inspired hardware designs realize neural principles in electronics to provide high-performing, energy-efficient frameworks for artificial intelligence. The Neural Engineering Framework (NEF) brings forth a theoretical framework for representing
Externí odkaz:
https://doaj.org/article/4ac9dc19a504401cbfeadfb51436232b