Title :
Modelling of biological neurons by artificial neural networks
Author :
Tandeitnik, P. ; Guterman, H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
Abstract :
A general approach for modeling biological neurons by means of ANNs is presented. This approach does not require any a-priori information about the system dynamics. A close-loop neural network architecture based on a multilayer feed forward network, is used as an alternative approach to standard system identification. The model can be employed to simulate the behavior of complex networks
Keywords :
backpropagation; biocontrol; brain models; closed loop systems; feedforward neural nets; multilayer perceptrons; neurophysiology; physiological models; artificial neural networks; biological neuron modelling; close-loop neural network architecture; complex networks; identification; multilayer feed forward network; Artificial neural networks; Backpropagation algorithms; Biological neural networks; Biological system modeling; Brain modeling; Feedforward neural networks; Feeds; Multi-layer neural network; Neural networks; Neurons;
Conference_Titel :
Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
Conference_Location :
Jerusalem
Print_ISBN :
0-7803-3330-6
DOI :
10.1109/EEIS.1996.566939
