DocumentCode
2546685
Title
Mathematical analysis of neural networks used in the solution of set selection problems
Author
Jeffries, Clark
Author_Institution
Dept. of Math. Sci., Clemson Univ., SC, USA
fYear
1988
fDate
24-26 Aug 1988
Firstpage
677
Lastpage
680
Abstract
The generalized neural network model of M. Cohen and S. Grossberg (1983) has been studied by many authors using Lyapunov-type functions. As an alternative, the author treats closely related dynamical systems (the gain functions are piecewise linear) with other dynamical-systems-theory machinery. It is shown that, by using a certain perturbation scheme, one can use such models with piecewise linear gain functions to solve a variety of set selection problems
Keywords
Lyapunov methods; neural nets; perturbation techniques; Lyapunov-type functions; dynamical systems; gain functions; neural networks; perturbation; set selection problems; Character generation; Gain; Intelligent networks; Linear systems; Machinery; Mathematical analysis; Mathematical model; Neural networks; Piecewise linear techniques; Tellurium;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1988. Proceedings., IEEE International Symposium on
Conference_Location
Arlington, VA
ISSN
2158-9860
Print_ISBN
0-8186-2012-9
Type
conf
DOI
10.1109/ISIC.1988.65512
Filename
65512
Link To Document