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In the proposed method, the reconstruction is executed on a partial sub-band independently and then the reconstructed spectrum is recombined into a complete spectrum to yield the conventional MFCC for recognition.
However, when the noisy y was preprocessed by the proposed method, the reconstruction based on OMP-PKS (the dashed blue line) was very effective.
In our experience with this method, the reconstruction always satisfies the projections, even if they're misaligned, so that insignificant refinement occurs from updating.
For the finite volume method, the reconstruction step is employed to obtain the states for the calculation of numerical fluxes at the faces.
From an exact iterative reconstruction method, the reconstruction problem is reformulated to incorporate the local tomography setup, the prior knowledge constraint and the representation of the image in a coarse basis.
Since numerical fluxes with second order accuracy in time are derived by the GRP method, the reconstruction steps for physical variables in the new scheme are halved compared with the traditional Runge Kutta discontinuous Galerkin (RK-DG) scheme.
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Therefore, the proposed method performs the reconstruction more adaptively than the conventional methods, and accurate restoration and resolution enhancement by our method can expected.
We propose a new method for the reconstruction of the signed distance function in the context of level set methods.
The most widely used method for the reconstruction of quantitative brain images using PET is filtered back projection, an analytical image reconstruction method.
Results show the validity of our method in the reconstruction of phylogenetic trees, where the Underlying Approach outperforms the current state of the art methods.
This work aims of assessing the method and the reconstruction technique for liver cases.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com