DocumentCode :
2813586
Title :
Authentic modeling of complex dynamics of biological systems by the manipulation of artificial intelligence
Author :
Falahian, Razieh ; Dastjerdi, Maryam Mehdizadeh ; Gharibzadeh, Shahriar
Author_Institution :
Dept. of Biomed. Eng., Amirkabir Univ. of Technol. (AUT), Tehran, Iran
fYear :
2015
fDate :
3-5 March 2015
Firstpage :
47
Lastpage :
52
Abstract :
The recent meteoric significant developments in the biological and medical sciences have been the culmination of substantial efforts devoted to precisely modeling the behavior of biological systems and their responses to various stimuli. The complicated interactions within varied components of biological systems as well as with their environments make them extremely complex nonlinear systems. The results of several contemporary relevant investigations have manifested their chaotic behavioral patterns. With the aim of modeling this specific behavior of bio-systems, we employ a particular multilayer feed-forward neural network. The distinctive feature of our modeling method, which makes it dominant within the modeling techniques, is training the select neural network with the chaotic map extracted from the under-study time series. Our results, which are briefly represented in this paper, confirm that the specified neural network does possess the potentiality to model the chaotic dynamics of biological systems., even in the presence of noise. In pursuance of evaluating our model, we assess and model the chaotic response of the brain to the flicker light through some recorded electroretinogram data.
Keywords :
artificial intelligence; chaos; electroretinography; feature extraction; medical signal processing; multilayer perceptrons; time series; artificial intelligence manipulation; biological system; chaotic dynamics; chaotic map extraction; complex dynamics modelling; complex nonlinear system; electroretinogram data; multilayer feed-forward neural network; time series; Bifurcation; Biological neural networks; Biological system modeling; Brain modeling; Chaos; Fuzzy control; Training; Artificial Neural Network; biological systems; brain; chaotic behavior; modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-8817-4
Type :
conf
DOI :
10.1109/AISP.2015.7123513
Filename :
7123513
Link To Document :
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