Digital filter bank implementation and signal classification on the basis of CUDA

The present paper discusses radio monitoring tasks and their solution using DFT-modulated filter banks. Filter bank software-hardware implementations are studied on the basis of Central Processing Unit (CPU) and Compute Unified Device Architecture (CUDA) with the use of Graphics Processing Unit (GPU...

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Veröffentlicht in:2015 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW) S. 93 - 97
Hauptverfasser: Klionskiy, D. M., Kaplun, D. I., Voznesenskiy, A. S., Gulvanskiy, V. V., Kupriyanov, M. S.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.02.2015
Schlagworte:
AdaBoost
Algorithm design and analysis
binary tree
Biomedical monitoring
CUDA
digital filter bank
Graphics processing units
Monitoring
radio monitoring
Random access memory
signal classification
software-hardware implementation
ISBN:9781479973057, 147997305X
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:The present paper discusses radio monitoring tasks and their solution using DFT-modulated filter banks. Filter bank software-hardware implementations are studied on the basis of Central Processing Unit (CPU) and Compute Unified Device Architecture (CUDA) with the use of Graphics Processing Unit (GPU). It is shown that CUDA technology is efficient for processing large datasets and outperforms computational results on CPU. The paper also considers signal classification in real time for different signal-to-noise ratios using a binary tree together with the iterative AdaBoost technique. Experiments show that it is possible to reach the total classification error of 10% for signals handled in radio monitoring tasks.
ISBN:9781479973057
147997305X
DOI:10.1109/EIConRusNW.2015.7102239