Chaos-Wavelet-Neural Network Models for Automated EEG-Based Diagnosis of the Neurological Disorders

In this keynote lecture the author presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for automated electroencephalogram (EEG)-based diagnosis of neurological disorders. The methodology is based on adroit integration of three different computing technologies and problem solving paradigms: neural networks, wavelets, and the chaos theory. Examples of the research performed by the authors and his associates for automated diagnosis of epilepsy, the Alzheimer’s Disease, and Attention Deficit Hyperactivity Disorder are discussed