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2D Deconvolution Using Adaptive Kernel
2019
Proceedings (MDPI)
An analysis tool using Adaptive Kernel to solve an ill-posed inverse problem for a 2D model space is introduced. It is applicable for linear and non-linear forward models, for example in tomography and image reconstruction. While an optimisation based on a Gaussian Approximation is possible, it becomes intractable for more than some hundred kernel functions. This is because the determinant of the Hessian of the system has be evaluated. The SVD typically used for 1D problems fails with
doi:10.3390/proceedings2019033006
fatcat:qeu2blkcqfdjxhh5cc6x6as53q