Fuzzy cellular systems for a new computational paradigm
Language
English
Obiettivo Specifico
3IT. Calcolo scientifico
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Issue/vol(year)
/10 (1997)
Publisher
Elsevier
Pages (printed)
47-52
Date Issued
1997
Subjects
Abstract
In this paper a new approach for processing arrays of data is proposed. It is based on fuzzy logic and the
concepts of cellular computation. Arrays of simple, identical processing elements (called fuzzy cells) are
defined by using fuzzy rules. Moreover, each fuzzy cell interacts with its local neighbors. The overall behavior
of these locally interacting fuzzy systems is used to process arrays of data. Some examples of practical
applications are proposed. Among these, the new approach is applied to image-processing problems, and to the
simulation of heat diffusion phenomena.
concepts of cellular computation. Arrays of simple, identical processing elements (called fuzzy cells) are
defined by using fuzzy rules. Moreover, each fuzzy cell interacts with its local neighbors. The overall behavior
of these locally interacting fuzzy systems is used to process arrays of data. Some examples of practical
applications are proposed. Among these, the new approach is applied to image-processing problems, and to the
simulation of heat diffusion phenomena.
Sponsors
This work was partially supported by the Italian
National Research Council (C.N.R.) under the special project "Reti neurali
per i sistemi di controllo".
National Research Council (C.N.R.) under the special project "Reti neurali
per i sistemi di controllo".
References
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networks: a survey. 7th IFAC Symposium on Ltwge Scale Systems
(LSS'95), pp. 53-58.
Chua, L. O. and Yang, L. (1988a) Cellular neural networks: theory. IEEE
Trans. CAS 35, 1257-1272.
Chua, L. O. and Yang, L. (1988b) Cellular neural networks: applications.
IEEE Trans. CAS 35, 1273-1290.
Chua, L. O., Yang, L. and Krieg, K. R. (1991) Signal processing using
cellular neural networks. Journal of VLSI Signal Processing 3, 25-51.
Fortuna, L., Manganaro, G., Muscato, G. and Nunnari, G. (1996) Parallel
simulation of cellular neural networks. Computers & Electrical
Engineering 22, 61-84.
Gonzalez, R. C. and Woods, R. E. (1992) Digital Image Processing.
Addison Wesley, Reading, MA.
SGS-Thomson Microelectronics (1994) Fuzzy Studio--WARP, Software
development tool. User manual v. 1.0.
Toffoli, T. and Margolus, N. (1987) Cellular Automata Machines: A New
Environment for Modeling. MIT, Cambridge, MA.
Wolfram, S. (1984) Computation theory of cellular automata. Communications
in Mathematical Physics 96, 15-57.
Zadeh, L. A. (1965) Fuzzy sets. Information and Control 8, 338-353.
networks: a survey. 7th IFAC Symposium on Ltwge Scale Systems
(LSS'95), pp. 53-58.
Chua, L. O. and Yang, L. (1988a) Cellular neural networks: theory. IEEE
Trans. CAS 35, 1257-1272.
Chua, L. O. and Yang, L. (1988b) Cellular neural networks: applications.
IEEE Trans. CAS 35, 1273-1290.
Chua, L. O., Yang, L. and Krieg, K. R. (1991) Signal processing using
cellular neural networks. Journal of VLSI Signal Processing 3, 25-51.
Fortuna, L., Manganaro, G., Muscato, G. and Nunnari, G. (1996) Parallel
simulation of cellular neural networks. Computers & Electrical
Engineering 22, 61-84.
Gonzalez, R. C. and Woods, R. E. (1992) Digital Image Processing.
Addison Wesley, Reading, MA.
SGS-Thomson Microelectronics (1994) Fuzzy Studio--WARP, Software
development tool. User manual v. 1.0.
Toffoli, T. and Margolus, N. (1987) Cellular Automata Machines: A New
Environment for Modeling. MIT, Cambridge, MA.
Wolfram, S. (1984) Computation theory of cellular automata. Communications
in Mathematical Physics 96, 15-57.
Zadeh, L. A. (1965) Fuzzy sets. Information and Control 8, 338-353.
Type
article
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