Optimized support vector machines for nonstationary signal classification
Optimized support vector machines for nonstationary signal classification
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DOI：
10.1109/lsp.2002.806070
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发表时间：
2002-12-01
影响因子：
3.9
通讯作者：
Rayner, PJW
中科院分区：
文献类型：
--
作者：
Davy, M;Gretton, A;Rayner, PJW
本文描述了一种有效的非平稳信号分类方法。介绍了一种支持向量机算法，并对其参数进行了原则性优化。仿真结果表明，我们的低复杂度方法比现有的非平稳信号分类方法具有更好的性能。
This letter describes an efficient method to perform nonstationary signal classification. A support vector machine (SVM) algorithm is introduced and its parameters optimized in a principled way. Simulations demonstrate that our low-complexity method outperforms state-of-the-art nonstationary signal classification techniques.