Name
Abstract | ||
|---|---|---|
A new approach to source localization in human brain, an important problem of neuroscience, is presented. A multiple neural network-based hierarchical decision making system is developed. Each network is assigned to an independent model, and the output is evaluated in the higher level of the decision making system. Utility functions are designed in the framework of decision making. The network with the highest utility value is selected as the best network, representing the best model in EEG based inverse mapping. Simulation results show that, the multiple neural network based decision making system has successfully produced preferred decisions in source localization. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ICNN.1997.611671 | 1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 |
Keywords | Field | DocType |
electroencephalography,decision theory,magnetoencephalography,neural network,artificial neural networks,neurophysiology,inverse problems,neuroscience,surgery,neural nets,decision support systems,neural networks | Neurophysiology,Computer science,Decision support system,Network simulation,Probabilistic neural network,Time delay neural network,Artificial intelligence,Decision theory,Inverse problem,Artificial neural network | Conference |
Citations | PageRank | References |
2 | 0.46 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Murat Sonmez | 1 | 2 | 0.80 |
| M. Sun | 2 | 356 | 65.69 |
| Ching-chung Li | 3 | 383 | 65.47 |
| Robert J. Sclabassi | 4 | 113 | 22.24 |