An ART network with fuzzy control for image data compression

Author

Wu, C.J. ; Sung, A.H. ; Soliman, H.S.

Author_Institution

Dept. of Comput. Sci., New Mexico Tech., Socorro, NM, USA

fYear

1994

fDate

26-29 Jun 1994

Firstpage

1743

Abstract

The application of a simplified ART1 (adaptive resonance theory 1) network with a fuzzy controller to image data compression is presented. The unique feature of a vigilance parameter of ART allows the direct control of the trade-off between compression ratio and image quality; the fuzzy controller can be used to adjust vigilance to seek a better compromise automatically. Furthermore, the decision table of this fuzzy controller is designed to guarantee convergence. Therefore, the network is insensitive to the given initial vigilance values. Simulations are performed, and the results indicate that this fuzzy-control-equipped, simplified ART1 network provides a promising technique for image data compression

Keywords

ART neural nets; convergence; data compression; decision tables; fuzzy control; fuzzy neural nets; image coding; ART1 network; adaptive resonance theory; compression ratio; compromise; convergence; ecision table; fuzzy controller; image data compression; image quality; initial value insensitivity; simulations; vigilance; Adaptive control; Automatic control; Convergence; Data compression; Fuzzy control; Image coding; Image quality; Programmable control; Resonance; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1896-X

Type

conf

DOI

10.1109/FUZZY.1994.343593

Filename

343593