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Vol. 24, Special Issue, August 2013, pp. 28-34




Identification of Multisensor Conversion Characteristic Using Neural Networks
Iryna TURCHENKO and Volodymyr KOCHAN

Research Institute of Intelligent Computer Systems, Ternopil National Economic University, 3 Peremoga Square, 46020, Ternopil, Ukraine
E-mail: itu@tneu.edu.ua, vk@tneu.edu.ua


Received: 15 May 2013   /Accepted: 16 August 2013   /Published: 30 August 2013

Digital Sensors and Sensor Sysstems


Abstract: A method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is described in this paper. The proposed method is based on the neural-based reconstruction (approximation or prediction) of surface points of multisensor conversion characteristic. Each neural network module reconstructs separate point of the surface. Our results show that the use of a Support Vector Machine (SVM) model allows improving the reconstruction accuracy of multisensor conversion characteristic. The reconstruction results obtained by SVM are compared with the results obtained by a multi-layer perceptron (MLP).


Keywords: Multisensor, Conversion characteristic, Neural networks.


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