The design of high-precision sensing devises becomes ever more difficult and expensive. At the same time, the need for precise calibration of these devices (ranging from tiny sensors to spaceâ€¦ (More)

Whenever we use devices to take measurements, calibration is indispensable. While the purpose of calibration is to reduce bias and uncertainty in the measurements, it can be quite difficult,â€¦ (More)

We study the question of reconstructing two signals f and g from their convolution y = f âˆ— g. This problem, known as blind deconvolution, pervades many areas of science and technology, includingâ€¦ (More)

Suppose that we have <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> sensors and each one intends to send a function <inline-formula> <tex-math notation="LaTeX">${g}_{i}$â€¦ (More)

We study the question of extracting a sequence of functions {fi, gi}i=1 from observing only the sum of their convolutions, i.e., from y = âˆ‘s i=1 fi âˆ— gi. While convex optimization techniques are ableâ€¦ (More)

2016 50th Asilomar Conference on Signals, Systemsâ€¦

2016

Suppose that one receives the superposition of r signals and each of them passes through an unknown channel, can we correctly recover the signals and their corresponding channels simultaneously fromâ€¦ (More)

Given a set of data, one central goal is to group them into clusters based on some notion of similarity between the individual objects. One of the most popular and widely-used approaches is K-meansâ€¦ (More)

Whenever we use devices to take measurements, calibration is indispensable. While the purpose of calibration is to reduce bias and uncertainty in the measurements, it can be quite difficult,â€¦ (More)

2017 International Conference on Sampling Theoryâ€¦

2017

We study the question of reconstructing a sequence of {f<inf>i</inf>, g<inf>i</inf>}<inf>i=1</inf><sup>s</sup> from the sum of their convolution, i.e., y =â€¦ (More)