论文信息 - Design of a Fast Learning Classifier for Sleep Apnea Database based on Fuzzy SVM - 字舞流文

Design of a Fast Learning Classifier for Sleep Apnea Database based on Fuzzy SVM

Kyoung-Joung Lee | Sooyong Lee | Erdenebayar Urtnasan

[1] Kyoung-Joung Lee,et al. Optimal Classifier for Detection of Obstructive Sleep Apnea Using a Heartbeat Signal , 2017, Int. J. Fuzzy Log. Intell. Syst..

[2] J. Platt. Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[3] Kyoung-Joung Lee,et al. The Classification of Electrocardiograph Arrhythmia Patterns using Fuzzy Support Vector Machines , 2011, Int. J. Fuzzy Log. Intell. Syst..

[4] Qi Cheng,et al. An Online Sleep Apnea Detection Method Based on Recurrence Quantification Analysis , 2014, IEEE Journal of Biomedical and Health Informatics.

[5] Sheng-De Wang,et al. Fuzzy support vector machines , 2002, IEEE Trans. Neural Networks.

[6] S. Y. Lee,et al. Fuzzy Support Vector Machine for Pattern Classification of Time Series Data of KOSPI200 Index , 2004 .

[7] Willis J. Tompkins,et al. A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[8] Hyo-Ki Lee,et al. Sleep Apnea Detection Using a Piezo Snoring Sensor: A Pilot study , 2014 .