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Different from solving the nonlinear Hamilton Jacobi equations with finite differences in traditional level set methods, we solve the linear convection equation and reinitialization equation using the characteristic Galerkin finite element method.
Section 7: By using the unification of the Bernstein-type polynomials and the Bernstein-Galerkin methods, we solve high even-order differential equations.
In order to make the comparisons fair among different methods, we solve the PDEs in Equations 15, 17, 18, 19, 24, 29, 35, and 40 by semi-implicit difference scheme based on their gradient descent equations.
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To illustrate the comparative performance of our method with existing methods, we solved the following eight problems.
To demonstrate the method, we solve several model problems selected from the fields of atomic and nuclear physics.
Finally, using dual decomposition method, we solve the problem and propose a distributed temporal-aware algorithm called TARC-SD that optimally allocates the shared bandwidth to the sources.
Finally, using primal dual method, we solve DNUM problem and propose a distributed algorithm called CA-DNUM that optimally allocates the shared bandwidth to video streams.
Then, based on Gröbner basis method, we solve the solution of polynomial equation directly, and then the attitude is calculated by back-substitution method.
To illustrate the reliability of this method, we solve some important equations of fractional order, and present numerical results of the present method to show convergence rate, applicability and reliability of this method.
In our self-consistent IMEX method, we solve the hydrodynamics equations inside the implicit block as part of the nonlinear function evaluation making use of the Jacobian-free Newton Krylov (JFNK) method [5], [20], [17].
To show convergence of the proposed method we solve Example 4.1 using shifted Legandre collocation method.
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