Title :
Epileptic EEG signal classification with marching pursuit based on harmony search method
Author :
Guo, Ping ; Wang, Jing ; Gao, X.Z. ; Tanskanen, Jarno M A
Author_Institution :
Lab. of Image Process. & Pattern Recognition, Beijing Normal Univ., Beijing, China
Abstract :
In Epilepsy EEG signal classification, the main time-frequency features can be extracted by using sparse representation with marching pursuit (MP) algorithm. However, the computational burden is so heavy that it is almost impossible to apply MP to real time signal processing. To reduce complexity of sparse representation, we propose to adopt harmony search method in searching the best atoms. Because harmony search method can find the best atoms in continuous time-frequency dictionary, the performance of epilepsy EEG signal classification is enhanced. The validity of this method is proved by experimental results.
Keywords :
electroencephalography; feature extraction; medical disorders; medical signal processing; search problems; signal classification; signal representation; time-frequency analysis; MP algorithm; continuous time-frequency dictionary; epileptic EEG signal classification; harmony search method; marching pursuit algorithm; sparse representation; time-frequency feature extraction; Accuracy; Classification algorithms; Dictionaries; Electroencephalography; Feature extraction; Matching pursuit algorithms; Training; Electroencephalogram; Harmony search method; Overcomplete dictionary; Seizure detection; Sparse representation;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377715
