Fuzzy systems in instrumentation: fuzzy signal processing

Author

Russo, Fabrizio

Author_Institution

Dept. of Electron. & Comput. Sci., Trieste Univ., Italy

Volume

45

Issue

2

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

683

Lastpage

689

Abstract

Digital processing of sensor information plays a key role in the design of intelligent instrumentation. This paper shows how the rapidly emerging technology of fuzzy systems can be applied to some important signal processing tasks such as data preprocessing and data classification. In this framework, the latest developments of a recently introduced family of rule-based fuzzy operators are proposed, and applications to the filtering of noisy 1-D and 2-D measurement data are presented. The application of fuzzy systems to data classification is investigated in the second part of the paper. For this purpose, a fuzzy network structure and a learning method are presented which are able to acquire the necessary information from a collection of measurement data

Keywords

computerised instrumentation; filtering theory; fuzzy systems; inference mechanisms; knowledge based systems; learning (artificial intelligence); pattern classification; 1D; 2D; data classification; data preprocessing; digital processing; filtering; fuzzy signal processing; fuzzy systems; instrumentation; intelligent instrumentation; learning; noisy measurement data; rule-based fuzzy operators; Data preprocessing; Filtering; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Instruments; Intelligent sensors; Signal processing; Working environment noise;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.492809

Filename

492809