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Application of wavelet transform in feature extraction and pattern recognition of wideband echoes 被引量:8
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作者 ZHAO Jianping HUANG Jianguo ZHANG Huafeng(College of Marine Engineering, Northwestern Polytechnical University Xi’an 710072) 《Chinese Journal of Acoustics》 1998年第3期213-220,共8页
A novel approach to extract edge features from wideband echo is proposed. The set of extracted features not only represents the echo waveform in a concise way, but also is sufficient and well suited for classification... A novel approach to extract edge features from wideband echo is proposed. The set of extracted features not only represents the echo waveform in a concise way, but also is sufficient and well suited for classification of non-stationary echo data from objects with different property.The feature extraction is derived from the Discrete Dyadic Wavlet Transform (DDWT) of the echo through the undecimated algorithm. The motivation we use the DDWT is that it is time-shift-invariant which is beneficial for localization of edge, and the wavelet coefficients at larger scale represent the main shape feature of echo, i.e. edge, and the noise and modulated high-frequency components are reduced with scale increased. Some experimental results using real data which contain 144 samples from 4 classes of lake bottoms with different sediments are provided. The results show that our approach is a prospective way to represent wideband echo for reliable recognition of nonstationary echo with great variability. 展开更多
关键词 MALLAT IEEE SP Application of wavelet transform in feature extraction and pattern recognition of wideband echoes
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