Title :
A neural networks approach to EEG signals modeling
Author :
Al-Nashash, Hasan A. ; Zalzala, Ali M S ; Thakor, Nitish V.
Author_Institution :
Sch. of Eng., Sharjah American Univ., United Arab Emirates
Abstract :
In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.
Keywords :
Markov processes; electroencephalography; neural nets; neurophysiology; EEG signal variations; EEG signals modeling; NN model; electoencephalography signals; first order Markov process amplitude model; hypoxic-ischemic cardiac arrest; neural networks approach; rodent brain injury; Biological neural networks; Biomedical engineering; Brain injuries; Brain modeling; Cardiac arrest; Electroencephalography; Markov processes; Neural networks; Power system modeling; Signal processing;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1280412
