Automated EEG-based diagnosis of neurological disorders : inventing the future of neurology /
Inventing the Future of Neurology based on the authors' groundbreaking research, this book presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integratio...
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| Format: | eBook |
| Language: | English |
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Boca Raton, FL :
CRC Press/Taylor & Francis,
©2010.
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Time-frequency analysis : wavelet transforms
- Chaos theory
- Classifier designs
- Electroencephalograms and epilepsy
- Analysis of EEGs in an epileptic patient using wavelet transform
- Wavelet-chaos methodology for analysis of EEGs and EEG sub-bands
- Mixed-band wavelet-chaos neural network methodology
- Principal component analysis-enhanced cosine radial basis function neural network
- Alzheimer's disease and models of computation : imaging, classification, and neural models
- Alzheimer's disease : models of computation and analysis of EEGs
- A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease
- Spiking neural networks : spiking neurons and learning algorithms
- Improved spiking neural networks with application to EEG classification and epilepsy and seizure detection
- A new supervised learning algorithm for multiple spiking neural networks
- Applications of multiple spiking neural networks : EEG classification and epilepsy and seizure detection.