128 / 2016-11-04 17:21:21
Specific emitter identification based on Fractal and Wavelet Theories
11726,11727,5967,8556
全文录用
欢欢 王 / 国家数字交换过程技术研究中心
Considering the characteristics of communication signal from the whole and local all together, it can improve the classification accuracy. A new feature extraction algorithm of communication signals based on the fractal and wavelet theories is proposed. Employing preprocessing the received signal, the correlation dimension of empirical mode decomposition(EMD) is researched to extract features and they are proved to be effective; As applying the wavelet method to communication signal analysis, The wavalet entropy characteristis which represent sources are extracted to be feature vectors. These features combining the correlation dimension and wavelet entropy are proved to be effective by identification experiment based on Support Vector Machine(SVM) classifier.
重要日期
  • 会议日期

    03月25日

    2017

    03月26日

    2017

  • 11月10日 2016

    初稿截稿日期

  • 11月20日 2016

    初稿录用通知日期

  • 11月30日 2016

    终稿截稿日期

  • 03月26日 2017

    注册截止日期

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