Fuzzy Temporal Sequence Processing By Fuzzified Recurrent Neural Fuzzy Network
نویسندگان
چکیده
Abstrad A Fuzzijed TSK-type Recurrent Neiiral Fuzzy Network (FTRNFN) for handling furry temporal information is proposed in this paper. The inputs and oulputs of FTRNFN are fuzzy pattems represented by Gaussian or isosceles triangular membership functions. In structure, FTRNFN is a recurrent fizzy nefwork constructed from a series of recurrent fuzzy +then rules with TSK-t)pe Consequent parts. The recurrent properly of FTRNFN eirables i f to deal with f u z v patterns .with temporal coilfat. fiere are 110 rules in FTRNFN iililia//y; they ore corrstnicted on-line by corrcurrent structure and parameter leanring. The abilil)' of TRFNFN is verr$edJkom a two-dinreusionol $my temporal sequence prediction problem.
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