Fuzzy Genetic Algorithms, SVM Methods for Epilepsy Classification

Language: English

Published by LAP LAMBERT Academic Publishing Mai 2012, 2012

3659133248 / 9783659133244

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This item is printed on demand - Print on Demand Titel. Neuware -Epileptic seizures result from a sudden electrical disturbance to the brain. Approximately one in every 100 persons will experience a seizure at some time in their life. In this work, we propose a genetic algorithm, SVM based fuzzy knowledge integration framework that is used for classification of risk level of epilepsy in diabetic patients from Electroencephalogram (EEG) signals. A statistical analysis of the EEG signal to indicate the onset of epilepsy based on chi square tests and control limits. Ten known diabetic patients with raw EEG recording are studied. Chapter 1 introduces the features of EEG signals and focus of the research. Chapter 2 discusses about Statistical analysis and quantification of Diabetic epilepsy risk through Chi-square tests. Chapter 3 reviews the fundamentals of fuzzy systems. Chapter 4 enumerates the Genetic algorithms for optimization of epilepsy risk levels. SVM techniques as a post classifier for epilepsy detection are discussed in Chapter 5. Results are discussed in Chapter 6. Chapter 7 brings out the conclusion. Chapter 8 shows the Future scope. This monograph is useful for all Engineering undergraduate, graduates students and practicing engineers.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch.…

Seller Inventory # 9783659133244

Title
Fuzzy Genetic Algorithms, SVM Methods for Epilepsy Classification
Author
Harikumar Rajaguru
Publisher
LAP LAMBERT Academic Publishing Mai 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659133248
ISBN 13
9783659133244
Item weight
191 grams
Dimensions
220x150x8 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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