DocumentCode :
2330341
Title :
Modified Freeman model: a stability analysis and application to pattern recognition
Author :
Ozturk, Mustafa C. ; Xu, Dongming ; Principe, José C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
Volume :
4
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
3207
Abstract :
The biologically realistic Freeman model of the olfactory cortex has been used to solve some engineering problems. However, due to the nature of the nonlinear function in the model, only numerical computer simulations can help explore the behavior of the system for different sets of control parameters. We modify the nonlinear function with a piecewise linear model and show that this simplified model exhibits the same qualitative behavior as the original one. Moreover, for this modified model, we employ the analytical tools of nonlinear dynamics to understand the system response for different parameter values. Finally, similar to the original system, we show that the modified system can be used as an auto-associative memory.
Keywords :
biology computing; content-addressable storage; control engineering computing; neurophysiology; nonlinear dynamical systems; pattern recognition; piecewise linear techniques; stability; autoassociative memory; modified Freeman model; nonlinear dynamics; pattern recognition; piecewise linear model; stability analysis; Application software; Biological system modeling; Brain modeling; Computer simulation; Nonlinear control systems; Numerical models; Olfactory; Pattern recognition; Piecewise linear techniques; Stability analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Conference_Location :
Budapest
ISSN :
1098-7576
Print_ISBN :
0-7803-8359-1
Type :
conf
DOI :
10.1109/IJCNN.2004.1381191
Filename :
1381191
Link To Document :
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