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Signal classification and software–hardware implementation of digital filter banks based on field-programmable gate arrays and compute unified device architecture

  • Software and Hardware for Pattern Recognition and Image Analysis
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Abstract

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.

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Authors and Affiliations

  1. Computer Science Department, St. Petersburg Electrotechnical University “LETI,”, ul. Professora Popova 5, St. Petersburg, 197376, Russia

    D. I. Kaplun, D. M. Klionskiy, V. V. Gulvanskiy, A. S. Voznesenskiy, A. M. Golubkov, V. V. Geppener & M. S. Kupriyanov

Authors
  1. D. I. Kaplun
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  2. D. M. Klionskiy
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  3. V. V. Gulvanskiy
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  4. A. S. Voznesenskiy
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  5. A. M. Golubkov
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  6. V. V. Geppener
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  7. M. S. Kupriyanov
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Corresponding author

Correspondence to D. M. Klionskiy.

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Dmitrii Kaplun, PhD, Associate Professor, senior researcher at St. Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia). In 2009 he defended his PhD thesis in digital signal processing at St. Petersburg Electrotechnical University “LETI.” The current research and academic work are concerned with digital filter banks, radio monitoring and hydroacoustic monitoring applications, filter bank implementation using FPGA and CUDA, MATLAB, digital filtering, distributed arithmetic, reconfigurable systems. Kaplun regularly takes part in different joint projects connected with hydroacoustic and radio signal processing, vibrational signal processing and analysis and software-hardware implementation of digital signal processing algorithms in radio monitoring and hydroacoustic monitoring applications. The most substantial results are in the fields of digital filtering, reconfigurable systems, digital filter bank design, radio monitoring and hydroacoustic monitoring system design. Kaplun was awarded special prizes by the Ministry of Education and Science of the Russian Federation for academic achievements. He is the author of more than 50 papers on digital signal processing.

Vyacheslav Gulvanskiy postgraduate student (faculty of Computer Science and Technology, Department of Automation and Control Processes), junior researcher at St. Petersburg Electrotechnical University “LETI” (St. Petersburg, Russia). Graduate of Saint Petersburg Electrotechnical University “LETI” (2013, Department of Automation and Control Processes). The current research and academic work are concerned with digital filter banks, radio monitoring and hydroacoustic monitoring applications, filter bank implementation using FPGA and CUDA, MATLAB, digital filtering, distributed arithmetic, reconfigurable systems. Gulvanskiy regularly takes part in different joint projects connected with hydroacoustic and radio signal processing, vibrational signal processing and analysis and software-hardware implementation of digital signal processing algorithms in radio monitoring and hydroacoustic monitoring applications. He is the author of 20 papers on digital signal processing.

Dmitry Klionskiy, PhD, Associate Professor, Deputy Dean for international affairs (faculty of Computer Technologies and Informatics), leading researcher at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia). In 2013 he defended his PhD thesis in applied mathematics and digital signal processing at Saint Petersburg Electrotechnical University “LETI”. The current research and academic work are concerned with adaptive signal processing (empirical mode decomposition (EMD), wavelet analysis, singular spectral analysis) and intellectual analysis of signals on the basis of Data Mining technique (segmentation, clustering, classification, mining association rules, sequential analysis). D. Klionskiy regularly takes part in different joint projects connected with telemetric signal processing, geophysical data processing and analysis and intellectual analysis of geophysical and telemetric data. The most substantial results are in the fields of adaptive signal processing and spectral analysis of signals including signal preprocessing (denoising, detrending, Hurst parameter estimation via EMD, time-frequency analysis, segmentation and clustering of signals). D. Klionskiy was awarded special prizes by the Ministry of Education and Science of the Russian Federation for academic achievements. He is the author of more than 80 papers on digital signal processing.

Alexander Voznesenskiy, postgraduate student (faculty of Computer Technologies and Informatics, Department of Software Engineering and Computer Applications), junior researcher at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia). Graduate of Saint Petersburg Electrotechnical University “LETI” (2013, Department of Software Engineering and Computer Applications). The current research and academic work are concerned with digital filter banks, radio monitoring and hydroacoustic monitoring applications, adaptive signal processing algorithms, spectral analysis, wavelets. A. Voznesenskiy regularly takes part in different joint projects connected with hydroacoustic and radio signal processing, vibrational signal processing and analysis and softwarehardware implementation of digital signal processing algorithms in radio monitoring and hydroacoustic monitoring applications. He is the author of 20 papers on digital signal processing.

Alexander Golubkov, postgraduate student (faculty of Computer Technologies and Informatics, Department of Software Engineering and Computer Applications), junior researcher at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia). Graduate of Saint Petersburg Electrotechnical University “LETI” (2015, Department of Software Engineering and Computer Applications). The current research and academic work are concerned with hydroacoustic monitoring applications, adaptive signal processing algorithms, spectral analysis, wavelets. A. Golubkov regularly takes part in different joint projects connected with hydroacoustic and radio signal processing, vibrational signal processing and analysis and software- hardware implementation of digital signal processing algorithms in radio monitoring and hydroacoustic monitoring applications. He is the author of 10 papers on digital signal processing.

Mikhail Kupriyanov, PhD, Dr. of Tech. Sci., Professor, graduate of Omsk Polytechnical University (Omsk, Russia). Dean of the faculty of Computer Science and Technology of Saint Petersburg Electrotechnical University “LETI” (since 2010), head of the department of Computer Science and Engineering of Saint Petersburg Electrotechnical University “LETI” (since 2014) In 1988 he defended his doctoral thesis in the field of microprocessors and signal processing and later was conferred the rank of full professor at Saint Petersburg State Electrotechnical University. At present, he is the head of a joint project with “Oceanpribor” devoted to the development of mathematical, software and hardware tools for hydroacoustic signal processing. He teaches Microprocessor systems, Digital signal processing and Software development. His scientific work is connected with microprocessor systems, embedded systems, parallel and distributed computing, digital signal processing, intellectual analysis of data, Data Mining techniques (classification, clustering, association rules, etc.), software and hardware development. M. Kupriyanov is the author and co-author of several books on microprocessor systems, digital signal processing, and Data mining. The outlook for the future is mainly connected with further investigation and development of Data Mining techniques and signal processing techniques for hydroacoustic applications. He is the author of more than 150 papers on digital signal processing, microprocessor systems, artificial intelligence, parallel computing, and embedded systems.

Geppener Vladimir, PhD, Dr. of Tech. Sci., Professor, graduate of Saint Petersburg Electrotechnical University, Department of Electric and Electronic Engineering (Saint Petersburg, Russia, 1962) and Saint Petersburg State University, Department of Mathematics and Mechanics (Saint Petersburg, Russia, 1979). In 2000 he defended his doctoral thesis in the field of artificial intelligence and signal processing and later was conferred the rank of full professor at Saint Petersburg State Electrotechnical University (2003). At present, he is working in the Research and Engineering Center of Saint Petersburg Electrotechnical University (Saint Petersburg, Russia) as a leading researcher. V. Geppener also works as a full professor in Saint-Petersburg Electrotechnical University and teaches Digital signal processing, Artificial Intelligence, and Speech recognition. In 1999–2005 he gave lectures on Digital signal processing at Petropavlovsk-Kamchatsky State University (Petropavlovsk- Kamchatsky, Russia) and taught Computational mathematics. V. Geppener’s scientific work is connected with acoustics, digital signal processing, intellectual analysis of data, speech processing, pattern recognition, and image analysis. He has developed several applications of acoustics and Data Mining. He was twice awarded special grants by the Russian Foundation for Basic Research (RFBR). V. Geppener is the author and co-author of several books on geophysics, fundamentals of signal processing, and wavelets. The outlook for the future is mainly connected with further investigation and development of Data Mining techniques with regard to acoustics and telemetric signal processing. He is the author of more than 200 papers on digital signal processing.

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Kaplun, D.I., Klionskiy, D.M., Gulvanskiy, V.V. et al. Signal classification and software–hardware implementation of digital filter banks based on field-programmable gate arrays and compute unified device architecture. Pattern Recognit. Image Anal. 26, 506–517 (2016). https://doi.org/10.1134/S1054661816030093

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