Shannon's sampling theorem provides a link between the continuous and the discrete
realms stating that bandlimited signals are uniquely determined by its values on a discrete …

We introduce and analyze a framework and corresponding method for compressed sensing
in infinite dimensions. This extends the existing theory from finite-dimensional vector spaces …

We propose a construction of new wavelet-like bases that are well suited for the
reconstruction and processing of optically generated Fresnel holograms recorded on CCD …

We present SplineDist, an instance segmentation convolutional neural network for
bioimages extending the popular StarDist method. While StarDist describes objects as …

Splines come in a variety of flavors that can be characterized in terms of some differential
operator L. The simplest piecewise-constant model corresponds to the derivative operator …

Optical imaging beyond the diffraction limit, ie, optical superresolution, has been studied
extensively in various contexts. This paper presents an overview of some mathematical …

We revisit wavelet theory starting from the representation of a scaling function as the
convolution of a B-spline (the regular part of it) and a distribution (the irregular or residual …

Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied method for finding sparse
solutions to ill-posed inverse problems. In this letter, we present a data-driven scheme for …

In cyber-physical systems (CPS), physical behaviors are typically controlled by digital
hardware. As a consequence, continuous behaviors are discretized by sampling and …

Abstract Knowledge about the rotation properties of space debris objects is essential for the
active debris removal missions, accurate re-entry predictions and to investigate the long …