Simulation modeling of neural-based method of multi-sensor output signal recognition

被引：2
|
作者：
Turchenko, I. [1 ]
Kochan, V. [1 ]
Sachenko, A. [1 ]
Kochan, R. [1 ]
Stepanenko, A. [1 ]
Daponte, P. [2 ]
Grimaldi, D. [3 ]
机构：
[1] Ternopil Acad Natl Econ, Res Inst Intelligent Comp Syst, 3 Peremoga Sq, UA-46004 Ternopol, Ukraine
[2] Univ Sannio, I-82100 Benevento, Italy
[3] Univ Calabria, Dept Elect Informat & Syst, I-87036 Arcavacata Di Rende, Italy
来源：
2006 IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE PROCEEDINGS, VOLS 1-5 | 2006年
关键词：
multi-parameter sensor; recognition; neural networks;
D O I：
10.1109/IMTC.2006.328653
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
The possibility of artificial neural network usage for recognition of a signal of a multi-parameter 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 Multi-parameter sensor signal recognition using MATLAB software are presented in the end of thispaper.
引用
收藏
页码：1530 / +
页数：2
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