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Image reconstruction algorithm for electrical capacitance tomography based on multi-dimensional support vector regression

机译:基于多维支持向量回归的电容层析成像图像重建算法

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A new method based on multi-dimensional support vector regression (MSVR) is presented to solve the ill-posed image reconstruction problem in electrical capacitance tomography (ECT). The MSVR with a hyper-spherical insensitive zone and IRWLS algorithm is firstly introduced to solve this problem. The neural networks have been reported to be applied to this kind of inverse problem. However, this method is known for serious over-fitting. MSVR has been proven to have all the advantages of neural networks, and can overcome the over-fitting problem. The proposed MSVR method in this paper is verified through typical flow patters image reconstruction. The results show that this method is an effective approach to solve image reconstruction for ECT, which is faster compared with the iterative methods and more accurate compared with the neural networks.
机译:提出了一种基于多维支持向量回归(MSVR)的新方法来解决电容层析成像(ECT)中不适定图像重建问题。为了解决这个问题,首先引入了具有超球形不敏感区域和IRRWS算法的MSVR。据报道,神经网络已应用于这种反问题。但是,这种方法因严重过拟合而闻名。事实证明,MSVR具有神经网络的所有优点,并且可以克服过度拟合的问题。通过典型的流图图像重建验证了本文提出的MSVR方法。结果表明,该方法是解决ECT图像重建的有效方法,与迭代方法相比,速度更快,与神经网络相比,精度更高。

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