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Research of multi sensor intelligent system signal fusion and reconstruction

机译：多传感器智能系统信号融合与重构研究

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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.
机译：本文研究了多功能传感器信号重构的一些关键技术。针对多功能传感器信号重构问题，提出了一种基于B样条和扩展卡尔曼滤波器的多功能传感器信号重构方法。研究了过程的逆模型方法，给出了估计信号重构精度和计算方法。提出了遗传算法来平衡多功能传感器信号的重构精度和计算基础。为了进一步减少大量的多功能传感器信号重构的采样工作量，提出了基于约简方法的聚类多功能传感器样本选择方法，以选择合理的分布，适用于逆训练数据模型。研究和开发多传感器智能系统的更有效处理方法是研究和分析多传感器信息融合理论的新方向。随着智能系统需求的不断提高，多传感器系统信息融合的研究越来越受到人们的关注。

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