• Journal of the Korean Mathematical Society
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• v.56 no.3
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• pp.689-701
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• 2019

We study the recovery results of ${\ell}_p$-constrained compressive sensing (CS) with $p{\geq}1$ via robust width property and determine conditions on the number of measurements for standard Gaussian matrices under which the property holds with high probability. Our paper extends the existing results in Cahill and Mixon from ${\ell}_2$-constrained CS to ${\ell}_p$-constrained case with $p{\geq}1$ and complements the recovery analysis for robust CS with ${\ell}_p$ loss function.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.761-772
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• 2008

The object of this study is to develop the model that solves the numerically difficult problems in hydraulic engineering and to demonstrate the applicability of this model by means of various test examples, such as, verification in the gradually varied unsteady condition, three steady flow problems with the change of bottom slope with exact solution, and frictional bed with analytical solution. The governing equation of this model is the integral form of the Saint-Venant equation satisfying the conservation laws, and finite volume method with the Riemann solver is used. The evaluation of the mass and momentum flux with the HLL Riemann approximate solver is executed. MUSCL-Hancock scheme is used to achieve the second order accuracy in space and time. This study introduce the new and simple technique to discretize the source terms of gravity and hydrostatic pressure force due to longitudinal width variation for the balance of quantity between nonlinear flux and source terms. The results show that the developed model's implementation is accurate, robust and highly stable in various flow conditions with source terms, and this model is reliable for one-dimensional applications in hydraulic engineering.