@inproceedings{613a68505c7b4efe99facac4553129bb,
title = "A decision tree SVM classification method based on the construction of ship-radiated noise multidimension feature vector",
abstract = "A decision tree support vector machine (SVM) classification method based on the construction of ship-radiated noise multidimension feature vector is proposed in this paper. Aimed at three kinds of ship targets (class I submarine, class II warship and class III merchant ship) radiated noise, the subband distribution feature vectors of their 1 1/2-spectrum and 2 1/2-spectrum, and scale-energy feature vector of them based on wavelet transform are constructed respectively. And then a 55-dimension comprehensive feature vector of the ship-radiated noise is constructed. On this basis, a 24-dimension feature vector is obtained by using K-L transform for feature optimization. Finally, support vector machine technique is applied for the classification and it enhances the classification accuracy.",
keywords = "classification, decision tree support vector machine, high-order spectrum, ship-radiated noise, wavelet transform",
author = "Zhao Chen and Haiyan Wang and Xiaohong Shen and Jun Bai and Zhengguo Liu",
year = "2011",
doi = "10.1109/ICSPCC.2011.6061624",
language = "英语",
isbn = "9781457708947",
series = "2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011",
booktitle = "2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011",
note = "2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011 ; Conference date: 14-09-2011 Through 16-09-2011",
}