Signal classification and software–hardware implementation of digital filter banks based on field-programmable gate arrays and compute unified device architecture
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- 作者：D. I. Kaplun ; D. M. Klionskiy ; V. V. Gulvanskiy…
- 关键词：wideband monitoring ; radio monitoring ; hydroacoustic monitoring ; digital filter bank ; FPGA ; CUDA technology ; classification ; wavelet transform ; neural networks ; DFT ; coefficients
- 刊名：Pattern Recognition and Image Analysis
- 出版年：2016
- 出版时间：July 2016
- 年：2016
- 卷：26
- 期：3
- 页码：506-517
- 全文大小：1,274 KB
- 刊物类别：Computer Science
- 刊物主题：Pattern Recognition
Image Processing and Computer Vision
Russian Library of Science - 出版者：MAIK Nauka/Interperiodica distributed exclusively by Springer Science+Business Media LLC.
- ISSN：1555-6212
- 卷排序：26
文摘
The paper is devoted to handling wideband monitoring tasks by discrete Fourier transform (DFT) modulated filter banks. Filter bank implementation is considered using CPU (Central Processing Unit) and CUDA (Compute Unified Device Architecture) based on GPUs (Graphics Processing Units). We show that CUDA is more efficient for big signal sets due to low temporal and computational costs. The paper also discusses signal classification in filter bank channels for different signal-to-noise ratios using binary decision trees (with the iterative Adaboost procedure) and neural networks. The total classification error in our experiments does not exceed 10%. The results can be extended and applied to hydroacoustic monitoring tasks.