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SIMULATED ANNEALING SCHEMES IN TRANSIENTLY CHAOTIC NEURAL NETWORK MODEL.

Authors :
Feng, Y. C.
Cai, X.
Source :
International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics; 7/30/2004, Vol. 18 Issue 17-19, p2579-2584, 6p
Publication Year :
2004

Abstract

A transiently chaotic neural network (TCNN) is an approximation method for combinatorial optimization problems. The evolution function of self-back connect weight, called annealing function, influences the accurate and search speed of TCNN model. This paper analyzes two common annealing schemes. Furthermore we proposed a new subsection exponential annealing function. Finally, we compared these annealing schemes in TSP problem. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02179792
Volume :
18
Issue :
17-19
Database :
Complementary Index
Journal :
International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics
Publication Type :
Academic Journal
Accession number :
14744089
Full Text :
https://doi.org/10.1142/S0217979204025701