no code implementations • 18 Nov 2019 • Hans Christian Jung, Johannes Maly, Lars Palzer, Alexander Stollenwerk
This work is concerned with the problem of recovering high-dimensional signals $\mathbf{x} \in \mathbb{R}^n$ which belong to a convex set of low-complexity from a small number of quantized measurements.
Information Theory Information Theory Probability 62B10 G.3
no code implementations • 9 May 2018 • Johannes Maly, Lars Palzer
A simple hard-thresholding operation is shown to be able to recover $L$ signals $\mathbf{x}_1,...,\mathbf{x}_L \in \mathbb{R}^n$ that share a common support of size $s$ from $m = \mathcal{O}(s)$ one-bit measurements per signal if $L \ge \log(en/s)$.
Information Theory Information Theory
