Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface
المؤلفون المشاركون
Xu, Yilu
Hua, Jing
Zhang, Hua
Hu, Ronghua
Huang, Xin
Liu, Jizhong
Guo, Fumin
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-11-25
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI).
To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework.
We first introduce an improved TSVM (ITSVM) method, in which a comprehensive feature of each sample consists of its common spatial patterns (CSP) feature and its geometric feature.
Moreover, we use the concave-convex procedure (CCCP) to solve the optimization problem of TSVM under a new balancing constraint that can address the unknown distribution of the unlabelled set by considering various possible distributions.
In addition, we propose an improved self-training TSVM (IST-TSVM) method that can iteratively perform CSP feature extraction and ITSVM classification using an expanded labelled set.
Extensive experimental results on dataset IV-a from BCI competition III and dataset II-a from BCI competition IV show that our algorithms outperform the other competing algorithms, where the sizes and distributions of the labelled sets are variable.
In particular, IST-TSVM provides average accuracies of 63.25% and 69.43% with the abovementioned two datasets, respectively, where only four positive labelled samples and sixteen negative labelled samples are used.
Therefore, our algorithms can provide an alternative way to reduce the calibration time.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xu, Yilu& Hua, Jing& Zhang, Hua& Hu, Ronghua& Huang, Xin& Liu, Jizhong…[et al.]. 2019. Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129374
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xu, Yilu…[et al.]. Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1129374
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xu, Yilu& Hua, Jing& Zhang, Hua& Hu, Ronghua& Huang, Xin& Liu, Jizhong…[et al.]. Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129374
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1129374
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر