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Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 4, Pages 1,701-1,716, DOI: https://doi.org/10.21307/ijssis-2017-728
License : (CC BY-NC-ND 4.0)
Received Date : 05-July-2014 / Accepted: 12-November-2014 / Published Online: 01-December-2014
This paper studies some key technology of multifunctional sensor signal reconstruction. The
multifunctional sensor signal reconstruction problem, presented a multifunctional sensor signal
reconstruction method based on B spline and the extended Calman filter. The method of inverse model
of the process was studied, gives a method to estimate signal reconstruction accuracy and computation.
Genetic algorithm is proposed to balance the multifunctional sensor signal reconstruction accuracy
and computation based on. In order to further reduce the sampling effort of large quantities of
multifunctional sensor signal reconstruction, is proposed based on the reduction method clustering
multifunctional sensor sample selection method, to select the reasonable distribution, suitable for
inverse training data model. A new direction to study the theory of multi sensor information fusion is to
design and analysis more efficient processing of multi sensor intelligent system is proposed and
developed. With the continuous improvement of the intelligent system requirements, research on
information fusion of multi-sensor system is affected by the people more and more attention.
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