DocumentCode
3289851
Title
Pattern recognition in olfactory systems: modeling and simulation
Author
Yao, Yong ; Freeman, Walter J.
Author_Institution
Dept. of Physiol., California Univ., Berkeley, CA, USA
fYear
1989
fDate
0-0 1989
Firstpage
699
Abstract
An attempt is made to understand the natural design principles that underlie the superior performance of biological olfactory systems in pattern recognition. The authors express these principles in mathematics, learning algorithms, and neuromorphic hardware. A diagram of the olfactory system and its mathematical model are presented to show how to implement the system by software and electronic hardware. Its capability for pattern classification is verified in an input-driven model olfactory bulb under an input correlation learning rule.<>
Keywords
biology computing; chemioception; digital simulation; pattern recognition; physiological models; input correlation learning rule; learning algorithms; modeling; neuromorphic hardware; olfactory systems; pattern recognition; simulation; Biological system modeling; Biomedical computing; Pattern recognition; Simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location
Washington, DC, USA
Type
conf
DOI
10.1109/IJCNN.1989.118655
Filename
118655
Link To Document