Talk · IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering · February 1, 2015
Digital filter bank implementation and signal classification on the basis of CUDA
Dmitry M. Klionskiy, Dmitrii Kaplun, Alexander S. Voznesensky, Vyacheslav V. Gulvanskiy, Mikhail S. Kupriyanov
Abstract
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.
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