FuGeNeSys: Sw and Hw implementation

Author

Russo, Marco

Author_Institution

Istituto di Inf. e Telecommun., Catania Univ., Italy

Volume

1

fYear

1997

fDate

27-23 May 1997

Firstpage

209

Abstract

The author shows the main characteristics of the tool called FuGeNeSys. Using the basic techniques of soft computing, FuGeNeSys allows supervised approximation and classification of multi-input/multi-output systems. It is also shown that by using recent results obtained in the field of fuzzy processors it is possible to design a multiprocessor card which will significantly accelerate the learning process

Keywords

MIMO systems; add-on boards; fuzzy neural nets; genetic algorithms; learning by example; multiprocessing systems; pattern classification; FuGeNeSys; MIMO systems; classification; fuzzy logic; fuzzy processors; genetic algorithms; hardware implementation; hybrid learning; learning process; machine learning; multi-input/multi-output systems; multiprocessor card; neural networks; soft computing; software implementation; supervised approximation; Acceleration; Computer networks; Fuzzy logic; Fuzzy neural networks; Genetic algorithms; Input variables; Machine learning; Neural networks; Optimization methods; Perturbation methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3755-7

Type

conf

DOI

10.1109/KES.1997.616908

Filename

616908