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 this paper. © 2006 IEEE.

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

Daponte, P.;Grimaldi, D.
2006-01-01

Abstract

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 this paper. © 2006 IEEE.
2006
0780393600
Multi-parameter sensor; Neural networks; Recognition; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/285309
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