"Efficient Least Squares Identification with SISO Takagi–Sugeno Models". "Fantuzzi, C. & Rovatti, R. In "Proc. 3rd IFAC Symposium on Intelligent Components and Instruments for Control Applications (SICICA '97)", pages "585–589", "Annecy, France", jun # "~9–11," , 1997. "Invited paper in the session entitled: ``Fuzzy Modeling''"
abstract   bibtex   
"In this paper we exploit the approximation capabilities of Takagi-Sugeno models to devise an identification procedure for Single-Input Single-Output systems, which minimizes the squared error between the model and the target. The adoption of a model featuring an increased locality allows a substantial reduction in the complexity of the identification phase in which samples are taken into account. Then, a data-independent mapping is devised to translate modified Takagi-Sugeno models into conventional ones."
@INPROCEEDINGS{CSR_SICICA97,
	AUTHOR=    {"Fantuzzi, Cesare and Rovatti, Riccardo"},
	TITLE=     {"Efficient Least Squares Identification with {SISO} {T}akagi--{S}ugeno Models"},
	BOOKTITLE= {"Proc. 3rd {IFAC} Symposium on Intelligent Components and Instruments for Control Applications (SICICA '97)"},
	YEAR=      {1997},
        pages = {"585--589"},
        address=   {"Annecy, France"},
        MONTH	= {jun # "~9--11," },
	ID=      {"199706"},
        note={"Invited paper in the session entitled: ``Fuzzy Modeling''"},
	ABSTRACT={"In this paper we exploit the approximation capabilities 
of Takagi-Sugeno models to devise an identification procedure for
Single-Input Single-Output systems, which minimizes the squared error
between the model and the target. The adoption of a model featuring an
increased locality allows a substantial reduction in the complexity of
the identification phase in which samples are taken into
account. Then, a data-independent mapping is devised to translate
modified Takagi-Sugeno models into conventional ones."}
}

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