Hormone secretion estimation using fuzzy deconvolution

Author

Boekhoudt, Piet

Author_Institution

Dept. of Math., Limburg Univ., Maastricht, Netherlands

Volume

3

fYear

1996

fDate

8-11 Sep 1996

Firstpage

1972

Abstract

In this paper we describe a fuzzy identification method to find the instantaneous secretion rate of a hormone. The dynamics of the relation between secretion rate and peripheral plasma hormone concentration is first identified by using learning signals. The fuzzy identification method is based on fuzzy clustering and optimal output predefuzzification. The proposed method leads to a fuzzy inference system which is able to perform the deconvolution, i.e. reconstruction of the unknown secretion rate. The results compare well with other deconvolution methods

Keywords

deconvolution; fuzzy systems; identification; inference mechanisms; learning (artificial intelligence); medical signal processing; time series; dynamics; fuzzy clustering; fuzzy deconvolution; fuzzy identification; fuzzy inference system; hormone secretion estimation; learning signals; optimal output predefuzzification; plasma hormone concentration; time series; Biochemistry; Deconvolution; Endocrine system; Fluids and secretions; Fuzzy systems; Neodymium; Plasma measurements; Signal processing; Takagi-Sugeno model; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.552720

Filename

552720