26,705 research outputs found
Wave splitting of Maxwell's equations with anisotropic heterogeneous constitutive relations
The equations for the electromagnetic field in an anisotropic media are
written in a form containing only the transverse field components relative to a
half plane boundary. The operator corresponding to this formulation is the
electromagnetic system's matrix. A constructive proof of the existence of
directional wave-field decomposition with respect to the normal of the boundary
is presented.
In the process of defining the wave-field decomposition (wave-splitting), the
resolvent set of the time-Laplace representation of the system's matrix is
analyzed. This set is shown to contain a strip around the imaginary axis. We
construct a splitting matrix as a Dunford-Taylor type integral over the
resolvent of the unbounded operator defined by the electromagnetic system's
matrix. The splitting matrix commutes with the system's matrix and the
decomposition is obtained via a generalized eigenvalue-eigenvector procedure.
The decomposition is expressed in terms of components of the splitting matrix.
The constructive solution to the question on the existence of a decomposition
also generates an impedance mapping solution to an algebraic Riccati operator
equation. This solution is the electromagnetic generalization in an anisotropic
media of a Dirichlet-to-Neumann map.Comment: 45 pages, 2 figure
Bounded perturbation resilience of projected scaled gradient methods
We investigate projected scaled gradient (PSG) methods for convex
minimization problems. These methods perform a descent step along a diagonally
scaled gradient direction followed by a feasibility regaining step via
orthogonal projection onto the constraint set. This constitutes a generalized
algorithmic structure that encompasses as special cases the gradient projection
method, the projected Newton method, the projected Landweber-type methods and
the generalized Expectation-Maximization (EM)-type methods. We prove the
convergence of the PSG methods in the presence of bounded perturbations. This
resilience to bounded perturbations is relevant to the ability to apply the
recently developed superiorization methodology to PSG methods, in particular to
the EM algorithm.Comment: Computational Optimization and Applications, accepted for publicatio
GMRES-Accelerated ADMM for Quadratic Objectives
We consider the sequence acceleration problem for the alternating direction
method-of-multipliers (ADMM) applied to a class of equality-constrained
problems with strongly convex quadratic objectives, which frequently arise as
the Newton subproblem of interior-point methods. Within this context, the ADMM
update equations are linear, the iterates are confined within a Krylov
subspace, and the General Minimum RESidual (GMRES) algorithm is optimal in its
ability to accelerate convergence. The basic ADMM method solves a
-conditioned problem in iterations. We give
theoretical justification and numerical evidence that the GMRES-accelerated
variant consistently solves the same problem in iterations
for an order-of-magnitude reduction in iterations, despite a worst-case bound
of iterations. The method is shown to be competitive against
standard preconditioned Krylov subspace methods for saddle-point problems. The
method is embedded within SeDuMi, a popular open-source solver for conic
optimization written in MATLAB, and used to solve many large-scale semidefinite
programs with error that decreases like , instead of ,
where is the iteration index.Comment: 31 pages, 7 figures. Accepted for publication in SIAM Journal on
Optimization (SIOPT
- …