Дослідження режимів вихідної генерації лінеаризованих штучних нейронів на базі апаратного рішення із ПЛІС архітектурою
Author:
Publisher
Kyiv Politechnic Institute
Subject
Electrical and Electronic Engineering,Computer Networks and Communications
Reference15 articles.
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2. P. Wilson, B. Metcalfe, J. Graham-Harper-Cater, and J. A. Bailey, “A reconfigurable architecture for real-time digital simulation of neurons,” in 2017 Intelligent Systems Conference, IntelliSys 2017, 2018, vol. 2018-January, pp. 66–75, doi: https://doi.org/10.1109/IntelliSys.2017.8324340.
3. Effects of the spike timing-dependent plasticity on the synchronisation in a random Hodgkin–Huxley neuronal network;Borges;Communications in Nonlinear Science and Numerical Simulation,2016
4. J. E. G-H-Cater, C. T. Clarke, B. W. Metcalfe, and P. R. Wilson, “A reconfigurable architecture for implementing locally connected neural arrays,” in Advances in Intelligent Systems and Computing, 2019, vol. 857, pp. 76–92, doi: https://doi.org/10.1007/978-3-030-01177-2_6.
5. A Data Path Design Tool for Automatically Mapping Artificial Neural Networks on to FPGA-Based Systems;Sahin;Journal of Electrical Engineering and Technology,2016-09-01
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