Optimal reconstruction of the solution of the Dirichlet problem from inaccurate input data

In this paper, we consider the optimal reconstruction of the solution of the Dirichlet problem in the d-dimensional ball on the sphere of radius r from inaccurately prescribed traces of the solution on the spheres of radii R ₁ and R ₂, where R ₁ < r < R ₂. We also study the optimal reconstruction of the solution of the Dirichlet problem in the d-dimensional ball from a finite collection of Fourier coefficients of the boundary function which are prescribed with an error in the mean-square and uniform metrics.     

Search for maximum points of a vector criterion based on decomposition properties

We address the problem of optimal reconstruction of the values of a linear operator on ℝ ^d or ℤ ^d from approximate values of other operators. Each operator acts as the multiplication of the Fourier transform by a certain function. As an application, we present explicit expressions for optimal methods of reconstructing the solution of the heat equation (for continuous and difference models) at a given instant of time from inaccurate measurements of this solution at other time instants.     

Solving of second order nonlinear PDE problems by using artificial controls with controlled error

In this paper, we find the approximate solution of a second order nonlinear partial differential equation on a simple connected region inR ². We transfer this problem to a new problem of second order nonlinear partial differential equation on a rectangle. Then, we transformed the later one to an equivalent optimization problem. Then we consider the optimization problem as a distributed parameter system with artificial controls. Finally, by using the theory of measure, we obtain the approximate solution of the original problem. In this paper also the global error inL ₁ is controlled.     

Numerical treatment of singularly perturbed two point boundary value problems using initial-value method

In this paper, we describe an initial-value method for linear and nonlinear singularly perturbed boundary value problems in the interval [p,q]. For linear problems, the required approximate solution is obtained by solving the reduced problem and one initial-value problems directly deduced from the given problem. For nonlinear problems the original second-order nonlinear problem is linearized by using quasilinearization method. Then this linear problem is solved as previous method. The present method has been implemented on several linear and non-linear examples which approximate the exact solution. We also present the approximate and exact solutions graphically.     

Higher order of fully discreate solution for parabolic problem inL ∞

In this work, we approximate the solution of initial boundary value problem using a Galerkin-finite element method for the spatial discretization, and Implicit Runge-Kutta methods for the time stepping. To deal with the nonlinear termf(x, t, u), we introduce the well-known extrapolation sheme which was used widely to prove the convergence inL ₂-norm. We present computational results showing that the optimal order of convergence arising underL ₂-norm will be preserved inL _∞-norm.     

Eventual periodicity of forced oscillations of the Korteweg-de Vries type equation

In this paper, we study the eventual periodicity of the initial boundary value problem (IBVP) for Korteweg-de Vries equation posed on a bounded domain. We show that if the boundary forcing is periodic of period τ, then the solution u of the IBVP at each spatial point becomes eventually time-periodic of period τ. In order to exhibit eventual periodicity, we approximate the solution of the IBVP using the Adomian decomposition method. We compare our work with the approximate solution of IBVP obtained by the homotopy perturbation method and present numerical experiments using Mathematica.     

Initial-boundary problem for the 1-D Euler-Boltzmann equations in radiation hydrodynamics

We study the initial-boundary value problem for the one dimensional EulerBoltzmann equation with reflection boundary condition. For initial data with small total variation, we use a modified Glimm scheme to construct the global approximate solutions(U_(△t,d), I_(△t,d)) and prove that there is a subsequence of the approximate solutions which is convergent to the global solution.     

A Gradient Flow Approach to Optimal Model Reduction of Discrete-Time Periodic Systems

This paper is concerned with the optimal model reduction for linear discrete periodic time-varying systems and digital filters. Specifically, for a given stable periodic time-varying model, we shall seek a lower order periodic time-varying model to approximate the original model in an optimal H ₂ norm sense. By orthogonal projections of the original model, we convert the optimal periodic model reduction problem into an unconstrained optimization problem. Two effective algorithms are then developed to solve the optimization problem. The algorithms ensure that the H ₂ cost decreases monotonically and converges to an optimal (local) solution. Numerical examples are given to demonstrate the computational efficiency of the proposed method. The present paper extends the optimal model reduction for linear time invariant systems to linear periodic discrete time-varying systems.     

Weighted Monte Carlo method for an approximate solution of the nonlinear coagulation equation

New weighted modifications of direct statistical simulation methods designed for the approximate solution of the nonlinear Smoluchowski equation are developed on the basis of stratification of the interaction distribution in a multiparticle system according to the index of a pair of interacting particles. The weighted algorithms are validated for a model problem with a known solution. It is shown that they effectively estimate variations in the functionals with varying parameters, in particular, with the initial number N ₀ of particles in the simulating ensemble. The computations performed for the problem with a known solution confirm the semiheuristic hypothesis that the model error is O(N ₀ ^?1 ). Estimates are derived for the derivatives of the approximate solution with respect to the coagulation coefficient.     

On Smoothing l1 Exact Penalty Function for Constrained Optimization Problems

This article introduces a smoothing technique to the l₁ exact penalty function. An application of the technique yields a twice continuously differentiable penalty function and a smoothed penalty problem. Under some mild conditions, the optimal solution to the smoothed penalty problem becomes an approximate optimal solution to the original constrained optimization problem. Based on the smoothed penalty problem, we propose an algorithm to solve the constrained optimization problem. Every limit point of the sequence generated by the algorithm is an optimal solution. Several numerical examples are presented to illustrate the performance of the proposed algorithm.     

A two-phase heuristic for the bottleneck k-hyperplane clustering problem

In the bottleneck hyperplane clustering problem, given n points in $\mathbb{R}^{d}$ and an integer k with 1≤k≤n, we wish to determine k hyperplanes and assign each point to a hyperplane so as to minimize the maximum Euclidean distance between each point and its assigned hyperplane. This mixed-integer nonlinear problem has several interesting applications but is computationally challenging due, among others, to the nonconvexity arising from the ? ₂-norm. After comparing several linear approximations to deal with the ? ₂-norm constraint, we propose a two-phase heuristic. First, an approximate solution is obtained by exploiting the ? _∞-approximation and the problem geometry, and then it is converted into an ? ₂-approximate solution. Computational experiments on realistic randomly generated instances and instances arising from piecewise affine maps show that our heuristic provides good quality solutions in a reasonable amount of time.     

The problem of recovering the permittivity coefficient from the modulus of the scattered electromagnetic field

Under consideration is the stationary system of equations of electrodynamics relating to a nonmagnetic nonconducting medium. We study the problem of recovering the permittivity coefficient ε from given vectors of electric or magnetic intensities of the electromagnetic field. It is assumed that the field is generated by a point impulsive dipole located at some point y. It is also assumed that the permittivity differs from a given constant ε₀ only inside some compact domain Ω ? R³ with smooth boundary S. To recover ε inside Ω, we use the information on a solution to the corresponding direct problem for the system of equations of electrodynamics on the whole boundary of Ω for all frequencies from some fixed frequency ω ₀ on and for all y ∈ S. The asymptotics of a solution to the direct problem for large frequencies is studied and it is demonstrated that this information allows us to reduce the initial problem to the well-known inverse kinematic problem of recovering the refraction index inside Ω with given travel times of electromagnetic waves between two arbitrary points on the boundary of Ω. This allows us to state uniqueness theorem for solutions to the problem in question and opens up a way of its constructive solution.     

Explicit solution of the finite time L2-norm polynomial approximation problem

The aim of this paper is to present a new approach to the finite time L₂-norm polynomial approximation problem. A new formulation of this problem leads to an equivalent linear system whose solution can be investigated analytically. Such a solution is then specialized for a polynomial expressed in terms of Laguerre and Bernstein basis.     

l k,s -Singular values and spectral radius of rectangular tensors

The real rectangular tensors arise from the strong ellipticity condition problem in solid mechanics and the entanglement problem in quantum physics. In this paper, we study the singular values/vectors problem of real nonnegative partially symmetric rectangular tensors. We first introduce the concepts of l ^k,s -singular values/vectors of real partially symmetric rectangular tensors. Then, based upon the presented properties of l ^k,s -singular values /vectors, some properties of the related l ^k,s -spectral radius are discussed. Furthermore, we prove two analogs of Perron-Frobenius theorem and weak Perron-Frobenius theorem for real nonnegative partially symmetric rectangular tensors.     

Ordinary differential equations on closed subsets of locally convex spaces with applications to fixed point theorems

The construction and convergence of an approximate solution to the initial value problem x′ = f(t, x), x(0) = x₀, defined on closed subsets of locally convex spaces are given. Sufficient conditions that guarantee the existence of an approximate solution are analyzed in relation to the Nagumo boundary condition used in the Banach space case. It is also shown that the Nagumo boundary condition does not guarantee the existence of an approximate solution. Applications to fixed point theorems for weakly inward mappings are given.     

A further study on inverse linear programming problems

In this paper we continue our previous study (Zhang and Liu, J. Comput. Appl. Math. 72 (1996) 261–273) on inverse linear programming problems which requires us to adjust the cost coefficients of a given LP problem as less as possible so that a known feasible solution becomes the optimal one. In particular, we consider the cases in which the given feasible solution and one optimal solution of the LP problem are 0–1 vectors which often occur in network programming and combinatorial optimization, and give very simple methods for solving this type of inverse LP problems. Besides, instead of the commonly used l₁ measure, we also consider the inverse LP problems under l_∞ measure and propose solution methods.     

Determination of an unknown coefficient in a nonlinear heat equation

The problem of determining an unknown term k(u) in the equation k(u)u_t=(k(u)u_x)_x is considered in this paper. Applying Tikhonov's regularization approach, we develop a procedure to find an approximate stable solution to the unknown coefficient from the overspecified data.     

Convergence estimates for the wavelet-Galerkin method: superconvergence at the node points

In this paper we consider a regular 1-periodic initial value problem and Galerkin approximate solutions in subspaces ν _t spanned by scaled translates of a basic function?. Our goal is to estimate the error when? is in a class of functions which we name . Herer is a regularity parameter andm is related with a property (the Strang and Fix condition) which determines the best order of accuracy in theL ²-norm of approximations from ν _h . Whenm=r, includes all scaling functions corresponding tor-regular multiresolution analyses ofL ²(?). We get the exact node values of the given initial condition as coefficients for the approximate initial data. With this procedure, the coefficients of the resulting Galerkin solution can give a very accurate approximation of the exact solution at the node points, provided that? has many vanishing moments. Since this property is not satisfied in general, we work with another modified basic function?* constructed from the integer translates of?. GlobalL ²-estimates are also obtained.     

Lattice Algorithms for Multivariate L ∞ Approximation in the Worst-Case Setting

We approximate d-variate functions from weighted Korobov spaces with the error of approximation defined in the L _∞ sense. We study lattice algorithms and consider the worst-case setting in which the error is defined by its worst-case behavior over the unit ball of the space of functions. A lattice algorithm is specified by a generating (integer) vector. We propose three choices of such vectors, each corresponding to a different search criterion in the component-by-component construction. We present worst-case error bounds that go to zero polynomially with n ^?1, where n is the number of function values used by the lattice algorithm. Under some assumptions on the weights of the function space, the worst-case error bounds are also polynomial in d, in which case we have (polynomial) tractability, or even independent of d, in which case we have strong (polynomial) tractability. We discuss the exponents of n ^?1 and stress that we do not know if these exponents can be improved.     

Second-kind integral equations for the Laplace-Beltrami problem on surfaces in three dimensions

The Laplace-Beltrami problem Δ_Γψ = f has several applications in mathematical physics, differential geometry, machine learning, and topology. In this work, we present novel second-kind integral equations for its solution which obviate the need for constructing a suitable parametrix to approximate the in-surface Green’s function. The resulting integral equations are well-conditioned and compatible with standard fast multipole methods and iterative linear algebraic solvers, as well as more modern fast direct solvers. Using layer-potential identities known as Calderón projectors, the Laplace-Beltrami operator can be pre-conditioned from the left and/or right to obtain second-kind integral equations. We demonstrate the accuracy and stability of the scheme in several numerical examples along surfaces described by curvilinear triangles.