We present a theoretical analysis of the CORSING (COmpRessed SolvING) method for the numerical approximation of partial differential equations based on compressed sensing. In particular, we show that the best s-term approximation of the weak solution of a PDE with respect to an orthonormal system of N trial functions, can be recovered via a Petrov-Galerkin approach using m N orthonormal test fu...

We consider self-similar measures µ with support in the interval 0 ≤ x ≤ 1 which have the analytic functions e i2πnx : n = 0, 1, 2,. .. span a dense subspace in L 2 (µ). Depending on the fractal dimension of µ, we identify subsets P ⊂ N 0 = {0, 1, 2,. .. } such that the functions {en : n ∈ P } form an orthonormal basis for L 2 (µ). We also give a higher-dimensional affine construction leading t...

This research concerns offline identification of acoustic characteristics of enclosures with second-order resonant dynamics and their modeling as linear dynamic systems. The applied models can be described by basis function expansions. The practical problem of acoustic echo in enclosures is used as the target problem to be addressed. It has been found out that the classical filters are ineffect...

The existence of (standard) Gauss quadrature rules with respect to a nonnegative measure dμ with support on the real axis easily can be shown with the aid of orthogonal polynomials with respect to this measure. Efficient algorithms for computing the nodes and weights of an n-point Gauss rule use the n × n symmetric tridiagonal matrix determined by the recursion coefficients for the first n orth...

In this paper we propose a method for the approximation of high-dimensional functions over finite intervals with respect to complete orthonormal systems polynomials. An important tool is multivariate classical analysis variance (ANOVA) decomposition. For low-dimensional structure, i.e., low superposition dimension, are able achieve reconstruction from scattered data and simultaneously understan...

In this paper we address the problem of approximating functions on a semi-in nite interval by truncated series of orthonormal generalized Laguerre functions. The generalized Laguerre functions contain two parameters, namely a scale factor and an order of generalization. The rate of convergence of a generalized Laguerre series depends on the choice of these parameters. Results concerning the det...

This paper investigates the mathematical background of multiresolution analysis in the specific context where the signal is represented by irregularly sampled data at known locations. The study is related to the construction of nested piecewise polynomial multiresolution spaces represented by their corresponding orthonormal bases. Using simple spline basis orthonormalization procedures involves...

Functions of one or more variables are usually approximated with a basis; a complete, linearly independent set of functions that spans an appropriate function space. The topic of this paper is the numerical approximation of functions using the more general notion of frames; that is, complete systems that are generally redundant but provide stable infinite representations. While frames are well-...