Solution of the Problem of Classification of Hydroacoustic Signals Based on Harmonious Wavelets and Machine Learning

Two types of real hydroacoustic signals of whales are classified based on the harmonic wavelet transform (HWT) coefficients (fast implementation), windowed Fourier transform (FT) (spectrogram), and conventional FT using the k-NN algorithm. The accuracy of the classification is estimated for various...

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Vydané v:	Pattern recognition and image analysis Ročník 30; číslo 3; s. 480 - 488
Hlavní autori:	Klionskii, D. M., Kaplun, D. I., Voznesensky, A. S., Romanov, S. A., Levina, A. B., Bogaevskiy, D. V., Geppener, V. V., Razmochaeva, N. V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Moscow Pleiades Publishing 01.07.2020 Springer Nature B.V
Predmet:	Algorithms Applied Problems Classification Computer Science Fourier transforms Image Processing and Computer Vision Machine learning Neural networks Pattern Recognition Signal classification Signal processing Speech processing Underwater acoustics Wavelet transforms Whales windowed Fourier transform spectrogram neural networks wavelet transform k-NN algorithm Fourier transform harmonic wavelets classification machine learning
ISSN:	1054-6618, 1555-6212
On-line prístup:	Získať plný text
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