Encoder Improvement for Simple Amplitude Fully Parallel Classifiers Based on Gray Codes

Procedia Engineering 2017
Sergejs Šarkovskis, Aleksandrs Jeršovs, Deniss Kolosovs, Elans Grabs

The present article describes functionality of real-time classifier usable for data flow statistical parameters calculations, different modulation types symbol detecting and in other applications, where the fastest association of input signals sample is required with one of the predefined categories. The effective implementation of encoder with high number of bits for fully parallel classifier is provided based on Gray codes (Gray, 1953). The work is concluded with comparative analysis of encoder standard implementation and its optimized version for FPGAs manufactured by Xilinx and Altera companies.

Atslēgas vārdi
FPGA; big data; simple amplitude classifier; Gray code
DOI
10.1016/j.proeng.2017.01.119
Hipersaite
http://www.sciencedirect.com/science/article/pii/S1877705817301194?via%3Dihub

Šarkovskis, S., Jeršovs, A., Kolosovs, D., Grabs, E. Encoder Improvement for Simple Amplitude Fully Parallel Classifiers Based on Gray Codes. No: Procedia Engineering, Latvija, Rīga, 19.-22. oktobris, 2016. Amsterdam, Netherlands: Elsevier Ltd., 2017, 604.-614.lpp. ISSN 1877-7058. Pieejams: doi:10.1016/j.proeng.2017.01.119

Publikācijas valoda
English (en)