In much of the literature on the solution of linear ill-posed operator equations, the operator equation is discretized and regularization methods are developed for the discretized problem so obtained, without discussing the ramification of these methods for the infinite-dimensional problem. In particular, these regularization methods may only be applicable to certain linear ill-posed operator equations. This paper discusses how regularization by a modified truncated singular value decomposition introduced in [21] for finite-dimensional problems can be extended to operator equations. In finite dimensions, this regularization method yields approximate solutions of higher quality than standard truncated singular value decomposition. Our analysis in a Hilbert space setting is of practical interest, because the solution method presented avoids introduction of discretization errors during the solution process. We discuss how to construct such problems with Chebfun.
