Simulation of digital filter banks and signal classification in wideband monitoring tasks

The paper is devoted to handling radio monitoring tasks (wideband monitoring tasks) in real time. We suggest a new multichannel modification of the weighted overlap-add algorithm (WOLA-algorithm) for processing vector (multichannel) signals and performing multichannel signal classification. Filter b...

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Veröffentlicht in:Automatic control and computer sciences Jg. 49; H. 5; S. 303 - 312
Hauptverfasser: Klionskiy, D. M., Kaplun, D. I., Gulvanskiy, V. V., Voznesenskiy, A. S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Allerton Press 01.09.2015
Schlagworte:
Computer Science
Control Structures and Microprogramming
LF-prototype filter
wideband monitoring
vector DFT
radio monitoring
weighted overlap-add algorithm
vector signal
wavelet transform
neural networks
digital filter bank
CUDA technology
DFT-coefficients
classification
ISSN:0146-4116, 1558-108X
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Beschreibung
Zusammenfassung:The paper is devoted to handling radio monitoring tasks (wideband monitoring tasks) in real time. We suggest a new multichannel modification of the weighted overlap-add algorithm (WOLA-algorithm) for processing vector (multichannel) signals and performing multichannel signal classification. Filter bank implementation is considered using computers based on the CUDA (Compute Unified Device Architecture) technology. We show that CUDA is efficient for large signal sets due to its low temporal costs. We study signal classification in filter bank channels for different signal-tonoise ratios using binary decision trees, the iterative procedure Adaboost, and neural networks. Our experiments provided a total classification error less than 10%.
ISSN:0146-4116
1558-108X
DOI:10.3103/S0146411615050065