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Single-trial event-related potential emotional classification based on compressed sensing

机译:基于压缩感知的单项事件相关的潜在情感分类

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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.
机译:在这项研究中,针对情感语音单项事件相关电位(ERP)信号的鲁棒分类方法得到了发展。基于压缩感知(CS)理论的分类方法。首先,我们使用CS理论来减少ERP信号的维数。其次,采用K-SVD方法重建ERP信号,以构建超完备的冗余字典。最后,通过计算重构样本和测试样本之间的残差对ERP信号进行分类。实验结果表明,该算法可以有效地对嘈杂的ERP信号进行分类,避免了信号识别中的特征提取过程。

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