Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques - Softcover

Gajula, Buchanna

 
9786206152965: Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Softcover
ISBN 10: 6206152960 ISBN 13: 9786206152965
Verlag: LAP LAMBERT Academic Publishing, 2023

Inhaltsangabe

Machine Learning Classification of Epileptic Seizures Based on Electroencephalogram using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques1 IntroductionEpilepsy is one of the serious neurological diseases in the world. Indeed, early detection of epileptic seizures will extend the life span of epileptic patients. In this regard, a lot of efforts has been done to predict epileptic seizures based on electroencephalography (EEG) signals. In literature, there are many feature-based seizure classification methods quoted. No method is proved perfectly in capturing a standard set of features with the dynamics of signals. It is a common neurological disorder caused by the abnormally rapid release of brain nerve cells that is characterized by seizures. The scalp or intracranial Electroencephalogram (EEG) signals obtained in the clinic typically exhibit characteristics such as chaos, nonlinearity, etc.Deep neural networks have made significant advances in the field of machine learning during the last era. The model can learn effective representations from raw data in both supervised and unsupervised contexts by creating a hierarchical or "deep" structure.

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Über die Autorin bzw. den Autor

Buchanna grew up as a daily wage laborer to support his family and had to work hard in getting an education to fulfill his dreams. Buchanna is an energized leader, Buchanan Gajula has a beautiful wife Swapna Gajula with two children master Hanish Gajula and Varshith Gajula. Dr.Gajula wants to be part of the change in society and mentor the youth.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
6206152960
ISBN 13 
9786206152965
Einband
Taschenbuch
Anzahl der Seiten
128
Kontakt zum Hersteller
Nicht verfügbar
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