Neuromorphic Hardware Applied in the Development of Low-Power IoTs *
Author:
Affiliation:
1. IFRJ,Dep. Gestão da Produção,Nilopolis,Brazil
2. UFRJ,Dep. de Eletrônica e Computação,Rio de Janeiro,Brazil
Funder
Instituto Federal do Rio de Janeiro
CNPq
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10070112/10069877/10070266.pdf?arnumber=10070266
Reference28 articles.
1. A 0.086-mm2 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28nm CMOS;frenkel;IEEE Transactions on Biomedical Circuits and Systems,2018
2. EE292E Lecture Notes, Lecture 5;markovic;Stanford University,2013
3. Neuromorphic electronic systems
4. SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation
5. Low power digital CMOS design;chandrakasan;University of California,1994
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