An optimal L1-minimization algorithm for stationary Hamilton-Jacobi equations
KAUST Grant NumberKUS-C1-016-04
Permanent link to this recordhttp://hdl.handle.net/10754/597541
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AbstractWe describe an algorithm for solving steady one-dimensional convex-like Hamilton-Jacobi equations using a L1-minimization technique on piecewise linear approximations. For a large class of convex Hamiltonians, the algorithm is proven to be convergent and of optimal complexity whenever the viscosity solution is q-semiconcave. Numerical results are presented to illustrate the performance of the method.
SponsorsThis material is based upon work supported by the National Science Foundation grant DMS-0510650.This publication is based on work supported by Award No. KUS-C1-016-04, made by King AbdullahUniversity of Science and Technology (KAUST).
PublisherInternational Press of Boston