Hardware implementation of real-time Extreme Learning Machine in FPGA: analysis of precision, resource occupation and performance,
2016,
Jose V. Frances-Villora ,
A. Rosado-Munoz ,
José M. Martínez-Villena ,
M. Bataller-Mompeán ,
Juan Fco. Guerrero ,
Marek Węgrzyn ,
Computers and Electrical Engineering, Vol. 51, 139--156, ISSN: 0045-7906,
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Słowa kluczowe: Embedded systems, Extreme Learning Machine - ELM, FPGA, Neural network hardware, Neural network training, On-chip machine learning
Kod: CZR-JCR
BibTeX
(pkt. 20)
DOI: 10.1016/j.compeleceng.2016.02.007