Stability of some super-resolution problems
The problem of computational super-resolution asks to recover fine
features of a signal from inaccurate and bandlimited data, using an
a-priori model as a regularization. I will describe several
situations for which sharp bounds for stable reconstruction are known,
depending on signal complexity, noise/uncertainty level, and available
data bandwidth. I will also discuss optimal recovery algorithms, and
some open questions.