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Feature extraction and classification for underwater target signals based on Hilbert-Huang transform theory

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Title Feature extraction and classification for underwater target signals based on Hilbert-Huang transform theory
 
Creator Hong, Yang
Yaan, Li
Guohui, Li
 
Subject Hilbert-Huang Transform theory
Underwater target signals
Feature extraction
Classification
 
Description 1272-1278
In order to realize feature extraction and classification for underwater target signals, instead of the empirical mode decomposition (EMD) method, a new Ensemble EMD (EEMD) is used in the Hilbert-Huang transform when underwater target signals are analyzed. By the EEMD and Hilbert-huang transform, some feature parameters are extracted and applied to the classification of underwater target signals from actual measure. These features include (i) the center frequency of the strongest intrinsic mode function, (ii) the energy difference between the high and low frequency, (iii) the instantaneous energy variation range. Simulation and experimental results show that there exist some differences between the different types of target signals. Those may offer a good solution for automatic recognition of underwater target signals.
 
Date 2016-10-18T06:10:48Z
2016-10-18T06:10:48Z
2016-10
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://nopr.niscair.res.in/handle/123456789/35712
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.45(10) [October 2016]