Application of linear graph embedding as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals-Reference-Cited by-同舟云学术

Application of linear graph embedding as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals

Published:2015-12-09 Issue: Volume: Page:
ISSN:0277-786X
Container-title:SPIE Proceedings
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Author:

Prabhakar Sunil Kumar,Rajaguru Harikumar

Publisher

SPIE

Reference4 articles.

1. Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency-Domain Features

2. Analysis of EEG records in an epileptic patient using wavelet transform

3. S. Yan, D. Xu, B. Zhang and H.J. Zhang, “Graph Embedding: A General Framework for Dimensionality Reduction”, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (2005).

4. Noninvasive Diabetes Mellitus Detection Using Facial Block Color With a Sparse Representation Classifier

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