TY  - BOOK
AU  - Asmaa Hamad Elsaied Mohamed
AU  - Aboulella Hassanien , 
AU  - Aly Aly Fahmy , 
AU  - Essam Halim Houssein , 
TI  - Application of swarm intelligence optimization for enhancing detection of epileptic seizures in EEG signals / 
PY  - 2018///
CY  - Cairo : 
PB  - Asmaa Hamad Elsaied Mohamed , 
KW  - EEG
KW  - Machine Learning
KW  - Swarm Intelligence
N1  - Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Computer Science; Issued also as CD
N2  - The thesis introduces a hybrid classification model using swarm optimization algorithms and support vector machines (SVMs) for automatic seizure detection in EEG. This proposed classification model consists of four main phases; namely,1) EEG pre-processing used to remove the noises from the EEG signals and decompose EEG signal into various sub-bands,2) feature extraction used to extract the EEG signal features from decomposed signal,3) Feature selection and classifier Parameters Optimization based swarm algorithms and 4) classification phase that is mainly used to analyze and classify the EEG signal into normal or abnormal
UR  - http://172.23.153.220/th.pdf
ER  -