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.