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, bibliogr. rys. tab. wykr. summ.
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