Simulation Modeling of Neural-Based Method of Multi-Sensor Output Signal Recognition

Author

Turchenko, I. ; Kochan, V. ; Sachenko, A. ; Kochan, R. ; Stepanenko, A. ; Daponte, P. ; Grimaldi, D.

Author_Institution

Res. Inst. of Intelligent Comput. Syst., Ternopil Acad. of Nat. Economy

fYear

2006

fDate

24-27 April 2006

Firstpage

1530

Lastpage

1535

Abstract

The possibility of artificial neural network usage for recognition of a signal of a multiparameter sensor (MPS), described by different mathematical models, is described in this paper. These mathematical models are developed for the cases, when MPS conversion characteristics have positive derivatives, negative derivatives and derivatives of different sign at similar and opposite increasing of MPS output signal. The model of neural network, used for recognition, as well as achieved results of simulation modeling of a multiparameter sensor signal recognition using MATLAB software are presented in the end of this paper

Keywords

neural nets; sensor fusion; signal detection; MATLAB software; artificial neural network; multiparameter sensor; multisensor output signal recognition; Algorithm design and analysis; Computational modeling; Gas industry; Instrumentation and measurement; Machine learning algorithms; Mathematical model; Multi-layer neural network; Neural networks; Pollution measurement; Sensor phenomena and characterization; multi-parameter sensor; neural networks; recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE

Conference_Location

Sorrento

ISSN

1091-5281

Print_ISBN

0-7803-9359-7

Electronic_ISBN

1091-5281

Type

conf

DOI

10.1109/IMTC.2006.328653

Filename

4124601