基于压缩感知的单试验事件相关潜在情绪分类

Xueying Zhang, Fenglian Li, Jiang Chang, Lixia Huang, Ying Sun, Shufei Duan
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引用次数: 1

摘要

本研究提出了一种鲁棒的情绪语音单试验事件相关电位(ERP)信号分类方法。基于压缩感知理论的分类方法。首先,我们利用CS理论对ERP信号进行降维处理。其次,利用K-SVD方法重构ERP信号,构造过完备冗余字典;最后,通过计算重构样本与测试样本之间的残差对ERP信号进行分类。实验结果表明,该算法能有效地对带有噪声的ERP信号进行分类,避免了信号识别中的特征提取过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-trial event-related potential emotional classification based on compressed sensing
In this study, a robust classification method for emotional speech single-trial event-related potential (ERP) signal was developed. The classification method based on compression sensing (CS) theory. First, we use CS theory to reduce the dimensionality of the ERP signal. Second, the ERP signal was reconstructed by using K-SVD method to construct the over-complete redundant dictionary. Finally, the ERP signal was classified by calculating the residuals between the reconstructed samples and the test samples. The experimental results show that the proposed algorithm can effectively classify the noisy ERP signal and avoid the feature extraction process in the signal recognition.
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