离散余弦变换在MEG信号解码中的应用

S. M. Kia, E. Olivetti, P. Avesani
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引用次数: 11

摘要

在这项研究中,我们提出离散余弦变换系数作为一组新的有效的特征来识别脑磁图记录中的脑活动模式。我们认为对脑电信号的时频表示计算DCT系数是一种有效的技术,可以在大脑解码任务中降低特征空间的维数而不失去判别能力。我们对单次MEG解码的分类结果表明,与标准方法相比,DCT是一种可行的方法,它通过保留信号在时间、频率和空间域的动态模式来提高解码精度。
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Discrete Cosine Transform for MEG Signal Decoding
In this study, we propose the discrete cosine transform coefficients as a new and effective set of features for recognizing patterns of brain activity in MEG recording. We claim that computing DCT coefficients on the time-frequency representation of MEG signals is an efficient technique to reduce the dimensionality of feature space without losing discriminative power in brain decoding tasks. Our classification results on single-trial MEG decoding suggest that DCT is a viable method comparing to standard methods and it improves decoding accuracy by preserving the dynamic patterns of signal in time, frequency and space domains.
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