期刊
DIGITAL SIGNAL PROCESSING
卷 20, 期 4, 页码 1256-1263出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.dsp.2009.10.024
关键词
Blue whale calls; Feature extraction; Classification; Pattern recognition; Short-time Fourier transform; Wavelet packet transform; Multilayer perceptron
Two new characterization methods based on the short-time Fourier and the wavelet packet transforms are proposed to classify blue whale calls. The vocalizations are divided into short-time overlapping segments before applying these transforms to each segment. Then, the feature vectors are constructed by computing the coefficient energies within two subbands in order to capture the AB phrase and D vocalization characteristics, respectively. Finally, a multilayer perceptron (MLP) is used to classify the vocalization into A, B and D classes. The proposed methods present high classification performance (86.25%) on the tested database. (C) 2009 Elsevier Inc. All rights reserved.
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