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http://dx.doi.org/10.5573/ieie.2014.51.7.209

Analysis of Features and Discriminability of Transient Signals for a Shallow Water Ambient Noise Environment  

Lee, Jaeil (Dept. of Ocean System Engineering, Jeju Nat'l University)
Kang, Youn Joung (Dept. of Ocean System Engineering, Jeju Nat'l University)
Lee, Chong Hyun (Dept. of Ocean System Engineering, Jeju Nat'l University)
Lee, Seung Woo (Sonar Systems PMO, Agency for Defense Development)
Bae, Jinho (Dept. of Ocean System Engineering, Jeju Nat'l University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.51, no.7, 2014 , pp. 209-220 More about this Journal
Abstract
In this paper, we analyze the discriminability of features for the classification of transient signals with an ambient noise in a shallow water. For the classification of the transient signals, robust features for the variance of a noise are required due to a low SNR under a marine environment. In the modelling the ambient noise in shallow water, theoretical noise model, Wenz's observation data from the shallow water, and Yule-walker filter are used. Discrimination of each feature of the transient signals with an additive ambient noise is analyzed by utilizing a Fisher score. As the analysis of a classification accuracy about the transient signals of 24 classes using the selected features with a high discriminability, the features selected in the environment without a noise relatively have a good classification accuracy. From the analyzed results, we finally select a total 16 features out of 28 features. The recognition using the selected features results in the classification accuracy of 92% in SNR 20dB using Multi-class SVM.
Keywords
Transient signal; Shallow water ambient noise; Feature extraction; Feature select;
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