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EEG brain signal classification for epileptic seizure disorder detection

Main Author: Satapathy, Sandeep Kumar,
Other Authors: Dehuri, Satchidananda,, Jagadev, Alok Kumar,, Mishra, Shruti,, ScienceDirect (Online service)
Format: eBook
Language: English
Published: London, United Kingdom : Academic Press, an imprint of Elsevier, 2019.
Physical Description: 1 online resource.
Subjects:
Epilepsy -- Diagnosis.
Electroencephalography.
Electrophysiological aspects of epilepsy.
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100 1 |a Satapathy, Sandeep Kumar,  |e author. 
245 1 0 |a EEG brain signal classification for epileptic seizure disorder detection /  |c Sandeep Kumar Satapathy, Satchidananda Dehuri, Alok Kumar Jagadev, Shruti Mishra. 
264 1 |a London, United Kingdom :  |b Academic Press, an imprint of Elsevier,  |c 2019. 
300 |a 1 online resource. 
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504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (ScienceDirect, viewed February 21, 2019). 
505 8 |a 1.5. Swarm Intelligence1.6. Tools for Feature Extraction; 1.7. Contributions; 1.8. Summary and Structure of Book; Chapter 2: Literature Survey; 2.1. EEG Signal Analysis Methods; 2.2. Preprocessing of EEG Signal; 2.3. Tasks of EEG Signal; 2.4. Classical vs Machine Learning Methods for EEG Classification; 2.5. Machine Learning Methods for Epilepsy Classification; 2.6. Summary; Chapter 3: Empirical Study on the Performance of the Classifiers in EEG Classification; 3.1. Multilayer Perceptron Neural Network; 3.1.1. MLPNN With Back-Propagation; 3.1.2. MLPNN With Resilient Propagation. 
505 8 |a 3.1.3. MLPNN With Manhattan Update Rule3.2. Radial Basis Function Neural Network; 3.3. Probabilistic Neural Network; 3.4. Recurrent Neural Network; 3.5. Support Vector Machines; 3.6. Experimental Study; 3.6.1. Datasets and Environment; 3.6.2. Parameters; 3.6.3. Results and Analysis; 3.7. Summary; Chapter 4: EEG Signal Classification Using RBF Neural Network Trained With Improved PSO Algorithm for Epilepsy Identification; 4.1. Related Work; 4.2. Radial Basis Function Neural Network; 4.2.1. RBFNN Architecture; 4.2.2. RBFNN Training Algorithm; 4.3. Particle Swarm Optimization. 
505 8 |a 4.3.1. Architecture4.3.2. Algorithm; 4.4. RBFNN With Improved PSO Algorithm; 4.4.1. Architecture of Proposed Model; 4.4.2. Algorithm for Proposed Model; 4.5. Experimental Study; 4.5.1. Dataset Preparation and Environment; 4.5.2. Parameters; 4.5.3. Results and Analysis; 4.6. Summary; Chapter 5: ABC Optimized RBFNN for Classification of EEG Signal for Epileptic Seizure Identification; 5.1. Related Work; 5.2. Artificial Bee Colony Algorithm; 5.2.1. Architecture; 5.2.2. Algorithm; 5.3. RBFNN With Improved ABC Algorithm; 5.3.1. Architecture of the Proposed Model. 
505 8 |a 5.3.2. Algorithm for the Proposed Model5.4. Experimental Study; 5.4.1. Dataset Preparation and Environment; 5.4.2. Parameters; 5.4.3. Result and Analysis; 5.4.4. Performance Comparison Between Modified PSO and Modified ABC Algorithm; 5.5. Summary; Chapter 6: Conclusion and Future Research; 6.1. Findings and Constraints; 6.2. Future Research Work; References; Index; Back Cover. 
650 0 |a Epilepsy  |x Diagnosis. 
650 0 |a Electroencephalography. 
650 0 |a Electrophysiological aspects of epilepsy. 
650 7 |a HEALTH & FITNESS / Diseases / General.  |2 bisacsh. 
650 7 |a MEDICAL / Clinical Medicine.  |2 bisacsh. 
650 7 |a MEDICAL / Diseases.  |2 bisacsh. 
650 7 |a MEDICAL / Evidence-Based Medicine.  |2 bisacsh. 
650 7 |a MEDICAL / Internal Medicine.  |2 bisacsh. 
650 7 |a Electroencephalography.  |2 fast. 
650 7 |a Electrophysiological aspects of epilepsy.  |2 fast. 
650 7 |a Epilepsy  |x Diagnosis.  |2 fast. 
655 4 |a Electronic books. 
700 1 |a Dehuri, Satchidananda,  |e author. 
700 1 |a Jagadev, Alok Kumar,  |e author. 
700 1 |a Mishra, Shruti,  |e author. 
710 2 |a ScienceDirect (Online service) 
776 0 8 |i Print version:  |a Satapathy, Sandeep Kumar  |t EEG Brain Signal Classification for Epileptic Seizure Disorder Detection  |d San Diego : Elsevier Science & Technology,c2019  |z 9780128174265. 
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