Missing-Data Classification with the Extended Full-Dimensional Gaussian Mixture Model: Applications to EMG-Based Motion Recognition

IEEE Transactions on Industrial Electronics

Volumn 62, Issue 8, 2015, Pages 4994-5005

  Ding, Qichuan ^a   Han, Jianda ^a   Zhao, Xingang ^a   Chen, Yang ^b  

^a SHENYANG INSTITUTE OF AUTOMATION   (China)

^b WUHAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Classification; Electromyography; Gaussian mixture model (GMM); Missing data; Myoelectric hand

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; ELECTROMYOGRAPHY; GAUSSIAN DISTRIBUTION; ONLINE SYSTEMS; PATTERN RECOGNITION; SOCIAL NETWORKING (ONLINE);

CLASSIFICATION ACCURACY; CONVERGENCE AND STABILITY; GAUSSIAN MIXTURE MODEL; MISSING DATA; MYOELECTRIC HAND; PATTERN RECOGNITION TECHNIQUES; REAL LIFE CLASSIFICATION; SURFACE ELECTROMYOGRAPHY;

CLASSIFICATION (OF INFORMATION);

EID: 84934324315     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2015.2403797     Document Type: Article

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