AbstractIn this paper, we consider the question of representing an entire function of finite order and type in terms of finitely many bits, and reconstructing the function from these. Instead of making any further assumptions about the function, we measure the error in reconstruction in a suitably weighted Lp norm. The optimal number of bits in order to obtain a given accuracy is given by the Kolmogorov entropy. We determine this entropy in the case of certain compact subsets of these weighted Lp spaces and obtain constructive algorithms to determine the asymptotically optimal bit representation from finitely many samples of the function. Our theory includes both equidistant and non-uniform sampling. The reconstructions are polynomials, hav...
The well-known Whittaker-Kotel'nikov-Shannon sampling theorem for frequency-bandlimited functions of...
We focus on the problem of representing a nonstationary finite-energy random field, with finitely ma...
AbstractWe prove that signals with bounded (r + 1)st derivative can be quantized using a uniform c-l...
AbstractIn this paper, we consider the question of representing an entire function of finite order a...
AbstractThis paper deals with the recovery of band- and energy-limited signals from a finite set of ...
AbstractThis paper deals with the recovery of band- and energy-limited signals in Lp(I)-norm from He...
According to the Kolmogorov complexity, every finite binary string is compressible to a shortest cod...
We address the problem of encoding signals which are sparse, i.e. signals that are concentrated on a...
This paper studies the stability of some reconstruction algorithms for compressed sensing in terms o...
This paper studies the stability of some reconstruction algorithms for compressed sensing in terms o...
This thesis is concerned with the problem of irregular sampling with derivatives. In one dimension, ...
This paper examines information-theoretic questions regarding the difficulty of compressing data ver...
In this paper we evaluate several methods of reconstructing signals from finite sets of their sample...
Suppose we are given a vector f in a class F ⊂ ℝN, e.g., a class of digital signals or digital imag...
AbstractAn algorithm is given for everywhere extrapolating a band-limited signal known only on an in...
The well-known Whittaker-Kotel'nikov-Shannon sampling theorem for frequency-bandlimited functions of...
We focus on the problem of representing a nonstationary finite-energy random field, with finitely ma...
AbstractWe prove that signals with bounded (r + 1)st derivative can be quantized using a uniform c-l...
AbstractIn this paper, we consider the question of representing an entire function of finite order a...
AbstractThis paper deals with the recovery of band- and energy-limited signals from a finite set of ...
AbstractThis paper deals with the recovery of band- and energy-limited signals in Lp(I)-norm from He...
According to the Kolmogorov complexity, every finite binary string is compressible to a shortest cod...
We address the problem of encoding signals which are sparse, i.e. signals that are concentrated on a...
This paper studies the stability of some reconstruction algorithms for compressed sensing in terms o...
This paper studies the stability of some reconstruction algorithms for compressed sensing in terms o...
This thesis is concerned with the problem of irregular sampling with derivatives. In one dimension, ...
This paper examines information-theoretic questions regarding the difficulty of compressing data ver...
In this paper we evaluate several methods of reconstructing signals from finite sets of their sample...
Suppose we are given a vector f in a class F ⊂ ℝN, e.g., a class of digital signals or digital imag...
AbstractAn algorithm is given for everywhere extrapolating a band-limited signal known only on an in...
The well-known Whittaker-Kotel'nikov-Shannon sampling theorem for frequency-bandlimited functions of...
We focus on the problem of representing a nonstationary finite-energy random field, with finitely ma...
AbstractWe prove that signals with bounded (r + 1)st derivative can be quantized using a uniform c-l...