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  1. link.aps.org

    Due to their sizeable Kolmogorov n-width, travel-wave problems have brought critical challenges to conventional model reduction techniques. This study aims to provide new insights into this problem by exploiting the Radon cumulative distribution transform (R-CDT) that emerged in the sector of computer vision science. By virtue of the unique property that nonlinear invertible R-CDT renders both ...
    Author:Jie Ren, William R. Wolf, Xuerui MaoPublished:2021
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  3. researchgate.net

    The Radon Cumulative Distribution Transform (RCDT) [37,38, 39] is a combination of the cumulative distribution transform (CDT) and the Radon transform. The Radon transform is used to reduce ...
  4. ui.adsabs.harvard.edu

    Traveling-wave problems, due to their sizable Kolmogorov n -width, have brought critical challenges to conventional model reduction techniques. This study aims to provide insights into this problem by exploiting the Radon cumulative distribution transform (R-CDT) [Kolouri, Park, and Rohde, IEEE Trans. Image Process. 25, 920 (2016), 10.1109/TIP.2015.2509419], which has emerged in the sector of ...
  5. researchgate.net

    this problem by exploiting the Radon cumulative distribution transform (R-CDT) [1] emerged in the sector of computer vision science. The core lies in the unique property of the nonlinear in-
  6. pure.bit.edu.cn

    In contrast to the physical space, a substantial model reduction is achieved in the R-CDT space while sustaining high accuracy. The method is parameter-free and data-driven and lends itself to problems regardless of the dimensions or boundary conditions.
  7. semanticscholar.org

    This work describes a nonlinear, invertible, low-level image processing transform based on combining the well-known Radon transform for image data, and the 1D cumulative distribution transform proposed earlier and shows that it can often render certain problems linearly separable in a transform space. Expand
  8. journals.aps.org

    Model reduction of traveling-wave problems via Radon cumulative distribution transform. Jie Ren, William R. Wolf, and Xuerui Mao. Phys. Rev. Fluids 6, L082501 (2021) - Published 17 August, 2021. Due to their sizeable Kolmogorov n-width, travel-wave problems have brought critical challenges to conventional model reduction techniques. This study ...
  9. Apr 28, 2023Problems with dominant advection, discontinuities, travelling features, or shape variations are widespread in computational mechanics. However, classical linear model reduction and interpolation methods typically fail to reproduce even relatively small parameter variations, making the reduced models inefficient and inaccurate. In this work a novel reduced order modelling approach is proposed ...
  10. link.springer.com

    However, classical linear model reduction and interpolation methods typically fail to reproduce even relatively small parameter variations, making the reduced models inefficient and inaccurate. This work proposes a model order reduction approach based on the Radon Cumulative Distribution Transform (RCDT). We demonstrate numerically that this ...
  11. semanticscholar.org

    This study aims to provide new insights into Travelling-wave problems by exploiting the Radon cumulative distribution transform (R-CDT) emerged in the sector of computer vision science, and shows the model reduction of travelling Gaussian solitons. Travelling-wave problems, due to their sizeable Kolmogorov n-width, have brought critical challenges to conventional model reduction techniques ...

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