کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4962261 1446527 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification Based on Multilayer Extreme Learning Machine for Motor Imagery Task from EEG Signals
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Classification Based on Multilayer Extreme Learning Machine for Motor Imagery Task from EEG Signals
چکیده انگلیسی

Classification of motor imagery electroencephalogram (EEG) is one of the most important technologies for BCI. To improve the accuracy, this paper introduces a classification system based on Multilayer Extreme Learning Machine (ML-ELM). In the system, the combination of PCA and LDA is chosen as the method of feature extraction and the ML-ELM is used to classify. The ML-ELM has not only the advantage which ELM has but also better performance than ELM. In the experiment, our method is compared with the methods based on ELM, such as kernel-ELM, Constrained-ELM and V-ELM, and some state-of-the-art methods on the same dataset. The experimental results show that ML-ELM is much more suitable for motor imagery EEG data and has better performance than the others.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 88, 2016, Pages 176-184
نویسندگان
, , , , ,