Single sensor detection and classification of multiple sources by higher-order spectra

2003 ◽  
Author(s):  
M.C. Dogan ◽  
J.M. Mendel
Keyword(s):  
Higher Order ◽  
Multiple Sources ◽  
Single Sensor ◽  
Higher Order Spectra ◽  
Sensor Detection

scholarly journals Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher-Order Spectra

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Necmettin Sezgin
Keyword(s):  
Electrical Potential ◽  
Higher Order ◽  
Electrical Potential Difference ◽  
Phase Coupling ◽  
Classification Result ◽  
Learning Machines ◽  
Emg Signal ◽  
Quadratic Phase ◽  
Higher Order Spectra

The analysis and classification of electromyography (EMG) signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are aggressive or normal actions. The EMG dataset was obtained from the machine learning repository. First, the aggressive and normal EMG activities were analyzed using bispectrum and the quadratic phase coupling of each EMG episode was determined. Next, the features of the analyzed EMG signals were fed into learning machines to separate the aggressive and normal actions. The best classification result was 99.75%, which is sufficient to significantly classify the aggressive and normal actions.

Modeling and fuzzy control of ER damper using higher order spectra

2006 ◽  
Author(s):  
Jeongmok Cho ◽  
Taegeun Jung ◽  
Dong-Hyeon Kim ◽  
Nam Huh ◽  
Tae-Whee Joung ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Higher Order ◽  
Er Damper ◽  
Higher Order Spectra

Analysis of epileptic EEG signals using higher order spectra

2009 ◽  
Vol 33 (1) ◽  
pp. 42-50 ◽  
Author(s):  
K. C. Chua ◽  
V. Chandran ◽  
U. Rajendra Acharya ◽  
C. M. Lim
Keyword(s):  
Higher Order ◽  
Eeg Signals ◽  
Higher Order Spectra
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