Analysis of bionic olfactory neural networks based on small-world networks view

Author

Zhang, Jin ; Li, Guang ; Freeman, Walter J.

Author_Institution

Nat. Lab. of Ind. Control Technol., Univ. of Zhejiang, Hangzhou

fYear

2008

fDate

25-27 June 2008

Firstpage

1537

Lastpage

1539

Abstract

To model mammalian olfactory neural systems, Kset models have been constructed by Prof. Walter J. Freeman. In K-set models, KIII model simulates the whole olfactory neural system and has novel characters different from conventional artificial neural networks, such as non-convergent ldquochaoticrdquo dynamics. Based on small-world networks view, the structural characteristics of KIII model are analyzed in this paper. Analytic results show some interesting results: (1) KIII model has large clustering coefficient; (2) there is the linear relationship between node number and characteristic path length in KIII model.

Keywords

biocybernetics; chemioception; neural nets; K-set models; KIII model; artificial neural networks; bionic olfactory neural networks; mammalian olfactory neural systems; nonconvergent chaotic dynamics; small-world networks view; Biological system modeling; Brain modeling; Chaos; Electroencephalography; Graph theory; Intelligent control; Negative feedback; Nerve fibers; Neural networks; Olfactory; clustering coefficient; olfactory neural network; small-world networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593148

Filename

4593148