DYNAMIC MEASUREMENTS ERROR CORRECTION ON A BASIS OF NEURAL NETWORK INVERSE MODEL OF A SENSOR |
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| Andrei S. Volosnikov, Aleksandr L. Shestakov |
- Abstract:
- The neural network inverse model of a sensor with the filtration of the sequentially recovered signal is considered. This model allows it to effectively correct the dynamic measurements error due to the deep mathematical processing of measurement data. The result of the experimental data processing of the dynamic temperature measurements validates the efficiency of the proposed model and the algorithm of the dynamic measurements error correction.
- Keywords:
- dynamic measurements error, neural network model, inverse sensor model, recovery of sensor input signal, dynamic measurements data processing
- Download:
- IMEKO-WC-2015-TC21-421.pdf
- DOI:
- -
- Event details
- Event name:
- XXI IMEKO World Congress
- Title:
Measurement in Research and Industry
- Place:
- Prague, CZECH REPUBLIC
- Time:
- 30 August 2015 - 04 September 2015