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Updated: May 7, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
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计算与MFCC和卷积神经网络相匹配

Andrés Lozano1, Enrique Nava1, María Dolores García Méndez2

  • 1Department of Communication Engineering, University of Málaga, Málaga, Spain.

PloS one
|December 31, 2024
PubMed
概括

使用卷积神经网络 (CNN) 与Mel-Frequency Cepstrum系数 (mfccNasalance) 的新方法提供了一种比传统方法更准确的方法来测量鼻. 这种方法在评估超鼻性时显示出临床应用的前景.

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