Conventional wisdom and common practice in acquisition and reconstruction of images from
frequency data follow the basic principle of the Nyquist density sampling theory. This …

A number of fundamental results in modern statistical theory involve thresholding estimators.
This survey paper aims at reconstructing the history of how thresholding rules came to be …

Let ℱ be a class of measurable functions f: S↦ 0, 1 defined on a probability space (S, A, P).
Given a sample (X 1,…, X n) of iid random variables taking values in S with common …

Recent results show that a relatively small number of random projections of a signal can
contain most of its salient information. It follows that if a signal is compressible in some …

This paper proves best known guarantees for exact reconstruction of a sparse signal f from
few non-adaptive universal linear measurements. We consider Fourier measurements …

The recently introduced theory of compressed sensing (CS) enables the reconstruction or
approximation of sparse or compressible signals from a small set of incoherent projections; …

Developing energy efficient strategies for the extraction, transmission, and dissemination of
information is a core theme in wireless sensor network research. In this paper we present a …

Compressive sampling (CS), also called compressed sensing, entails making observations
of an unknown signal by projecting it onto random vectors. Recent theoretical results show …

This paper shows that near optimal rates of aggregation and adaptation to unknown sparsity
can be simultaneously achieved via ℓ 1 penalized least squares in a nonparametric …

Compressive sampling (CS), or" compressed sensing," has recently generated a
tremendous amount of excitement in the image processing community. CS involves taking a …