基于支持向量机的非平稳信号分类

信号处理 Pub Date : 2001-08-06 DOI:10.1109/SSP.2001.955283

Arthur Gretton, Manuel Davy, A. Doucet, P. Rayner

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引用次数: 7

摘要

我们演示了使用支持向量(SV)技术对二次相位的非平稳正弦信号进行二值分类。我们简要描述了SV分类的理论基础，并引入了Cohen的群时频表示，该表示用于处理非平稳信号以定义分类器输入空间。我们证明了SV分类器在处理过的数据上优于其他分类方法。

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Nonstationary signal classification using support vector machines

We demonstrate the use of support vector (SV) techniques for the binary classification of nonstationary sinusoidal signals with quadratic phase. We briefly describe the theory underpinning SV classification, and introduce Cohen's group time-frequency representation, which is used to process the nonstationary signals so as to define the classifier input space. We show that the SV classifier outperforms alternative classification methods on this processed data.

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来源期刊

信号处理

自引率

0.00%

发文量

5812

期刊介绍： Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.