DocumentCode
1664559
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
fYear
1996
Firstpage
239
Lastpage
242
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
Conference_Location
Jerusalem
Print_ISBN
0-7803-3330-6
Type
conf
DOI
10.1109/EEIS.1996.566939
Filename
566939
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