The Regularized Orthogonal Functional Matching Pursuit for Ill-Posed Inverse Problems
DOI10.1137/141000695zbMath1382.65162OpenAlexW2258628301MaRDI QIDQ5745017
Publication date: 11 February 2016
Published in: SIAM Journal on Numerical Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/141000695
inverse problemregularizationmultiresolution analysisspheregreedy algorithmscattered datanonlinear approximationill-posedmatching pursuitdownward continuation
Inverse problems in geophysics (86A22) Numerical methods for inverse problems for integral equations (65R32) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21) Boundary value and inverse problems for harmonic functions in higher dimensions (31B20) Numerical solution to inverse problems in abstract spaces (65J22)
Related Items (10)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Spline multiresolution and numerical results for joint gravitation and normal-mode inversion with an outlook on sparse regularisation
- A non-linear approximation method on the sphere
- An integrated wavelet concept of physical geodesy
- Spherical spline interpolation - basic theory and computational aspects
- On the computation of nonnegative quadrature weights on the sphere
- A survey on spherical spline approximation
- Lectures on constructive approximation. Fourier, spline, and wavelet methods on the real line, the sphere, and the ball
- Spherical wavelet transform and its discretization
- Spherical harmonics
- Sparse regularization of inverse gravimetry—case study: spatial and temporal mass variations in South America
- Spline Interpolation and Smoothing on the Sphere
- On spherical spline interpolation and approximation
- An iterative method for solving incorrectly posed problems
- Regularization wavelets and multiresolution
- Matching pursuits with time-frequency dictionaries
- Kernel matching pursuit
This page was built for publication: The Regularized Orthogonal Functional Matching Pursuit for Ill-Posed Inverse Problems