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The successful discrimination of depression from EEG could be attributed to proper feature extraction and not to a particular classification method

机译：成功歧视EEG的抑郁症可以归因于适当的特征提取，而不是特定的分类方法

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Milena Čukić; Miodrag Stokić; Slobodan Simić; Dragoljub Pokrajac;
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3. Comparison of Multi-Class Methods of Features Extraction and Classification to Recognize EEGs Related with the Imagination of Two Vowels [J] . Nicolas Marrugo, Dario Amaya, Olga Ramos International Journal on Communications Antenna and Propagation . 2018,第5期

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4. EEG-based automatic emotion recognition: Feature extraction, selection and classification methods [C] . Pascal Ackermann, Christian Kohlschein, Jó Ágila Bitsch, IEEE International Conference on e-Health Networking, Applications and Services . 2016

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5. GPR methods for the detection and characterization of fractures and karst features: Polarimetry, attribute extraction, inverse modeling and data mining techniques. [D] . Sassen, Douglas Spencer. 2009

机译：用于检测和表征裂缝和岩溶特征的GPR方法：旋光法，属性提取，逆建模和数据挖掘技术。
6. The successful discrimination of depression from EEG could be attributed to proper feature extraction and not to a particular classification method [O] . Milena Čukić, Miodrag Stokić, Slobodan Simić, 2020

机译：成功歧视EEG的抑郁症可以归因于适当的特征提取而不是特定的分类方法
7. Effective and Extensible Feature Extraction Method Using Genetic Algorithm-Based Frequency-Domain Feature Search for Epileptic EEG Multi-classification [O] . Wen, Tingxi, Zhang, Zhongnan 2017

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8. Signal Representation, Attribute Extraction and, the Use of Distinctive Features for Phonetic Classification. [R] . Meng, H. M., Zue, V. W., Leung, H. C. 1991

机译：信号表示，属性提取和语音分类特征的使用。

The successful discrimination of depression from EEG could be attributed to proper feature extraction and not to a particular classification method

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