Title :
FuGeNeSys: Sw and Hw implementation
Author_Institution :
Istituto di Inf. e Telecommun., Catania Univ., Italy
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;
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
DOI :
10.1109/KES.1997.616908
