Performance Analysis of ApEn as a Feature Extraction Technique and Time Delay Neural Networks, Multi Layer Perceptron as Post Classifiers for the Classification of Epilepsy Risk Levels from EEG Signals-Reference-Cited by-同舟云学术

Performance Analysis of ApEn as a Feature Extraction Technique and Time Delay Neural Networks, Multi Layer Perceptron as Post Classifiers for the Classification of Epilepsy Risk Levels from EEG Signals

Published:2015-12-19 Issue: Volume: Page:89-97
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
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Author:

Prabhakar Sunil Kumar,Rajaguru Harikumar

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-0251-9_10

Reference14 articles.

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2. Harikumar, R., Vijayakumar, T.: Wavelets and morphological operators based classification of epilepsy risk levels. Math. Probl. Eng. 2014(813197), 13 pp. (2014). doi: 10.1155/2014/813197

3. Gotman, J.: Automatic recognition of epileptic seizures in the EEG. Electroencephalogr. Clin. Neurophysiol. 54, 530–540 (1982)

4. Finley, K.H., Dynes, J.B.: Electroencephalographic studies in epilepsy: a critical analysis. Brain 65, 256–265 (1942)

5. Leon C.: Time-frequency distributions—a review. In: Proceedings of the IEEE, vol. 77, no. 7 (1989)

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