Inverse Problems Lecture 6/2017: building a matrix model for tomography

This is screen capture of Matlab programming I did when teaching my course Inverse Problems at University of Helsinki.

The lecture was given at February 3, 2017.

Here I construct a matrix model m=Af using Matlab's radon.m routine. The matrix is constructed column by column by applying radon.m consecutively to unit vectors. While computationally inefficient, this approach provides an easy way for constructing system matrices for tomographic problems. The matrix A can then be studied by, for example, singular value decomposition.