795 citations · 1.4k across the 64 of their papers we have counts for
9 papers · 1 filter
Frames and numerical approximation
Ben Adcock, Daan Huybrechs
Functions of one or more variables are usually approximated with a basis: a complete, linearly-independent system of functions that spans a suitable function space. The topic of th…
Analyzing the structure of multidimensional compressed sensing problems through coherence
Alex Jones, Ben Adcock, Anders Hansen
Recently it has been established that asymptotic incoherence can be used to facilitate subsampling, in order to optimize reconstruction quality, in a variety of continuous compress…
Uniform Recovery from Subgaussian Multi-Sensor Measurements
Il Yong Chun, Ben Adcock
Parallel acquisition systems are employed successfully in a variety of different sensing applications when a single sensor cannot provide enough measurements for a high-quality rec…
Optimal sampling rates for approximating analytic functions from pointwise samples
Ben Adcock, Rodrigo Platte, Alexei Shadrin
We consider the problem of approximating an analytic function on a compact interval from its values at distinct points. When the points are equispaced, a recent result (the s…
Computing reconstructions from nonuniform Fourier samples: Universality of stability barriers and stable sampling rates
Ben Adcock, Milana Gataric, José Luis Romero
We study the problem of recovering an unknown compactly-supported multivariate function from samples of its Fourier transform that are acquired nonuniformly, i.e. not necessarily o…
Sparsity and Parallel Acquisition: Optimal Uniform and Nonuniform Recovery Guarantees
Il Yong Chun, Chen Li, Ben Adcock
The problem of multiple sensors simultaneously acquiring measurements of a single object can be found in many applications. In this paper, we present the optimal recovery guarantee…
Optimal Sparse Recovery for Multi-Sensor Measurements
Il Yong Chun, Ben Adcock
Many practical sensing applications involve multiple sensors simultaneously acquiring measurements of a single object. Conversely, most existing sparse recovery guarantees in compr…
Compressed Sensing and Parallel Acquisition
Il Yong Chun, Ben Adcock
Parallel acquisition systems arise in various applications in order to moderate problems caused by insufficient measurements in single-sensor systems. These systems allow simultane…
Compressed sensing with local structure: uniform recovery guarantees for the sparsity in levels class
Chen Li, Ben Adcock
In compressed sensing, it is often desirable to consider signals possessing additional structure beyond sparsity. One such structured signal model - which forms the focus of this p…