338 citations · 2.1k across the 62 of their papers we have counts for
8 papers · 1 filter
Guaranteed blind deconvolution and demixing via hierarchically sparse reconstruction
Axel Flinth, Ingo Roth, Benedikt Groß +2
The blind deconvolution problem amounts to reconstructing both a signal and a filter from the convolution of these two. It constitutes a prominent topic in mathematical and enginee…
Hierarchical sparse recovery from hierarchically structured measurements with application to massive random access
Benedikt Groß, Axel Flinth, Ingo Roth +2
A new family of operators, coined hierarchical measurement operators, is introduced and discussed within the well-known hierarchical sparse recovery framework. Such operator is a c…
Hierarchical compressed sensing
Jens Eisert, Axel Flinth, Benedikt Groß +2
Compressed sensing is a paradigm within signal processing that provides the means for recovering structured signals from linear measurements in a highly efficient manner. Originall…
Hierarchical Isometry Properties of Hierarchical Measurements
Axel Flinth, Benedikt Groß, Ingo Roth +2
A new class of measurement operators, coined hierarchical measurement operators, and prove results guaranteeing the efficient, stable and robust recovery of hierarchically structur…
Performance of Hierarchical Sparse Detectors for Massive MTC
Gerhard Wunder, Ingo Roth, Rick Fritschek +1
Recently, a new class of so-called \emph{hierarchical thresholding algorithms} was introduced to optimally exploit the sparsity structure in joint user activity and channel detecti…
Hierarchical restricted isometry property for Kronecker product measurements
I. Roth, A. Flinth, R. Kueng +2
Hierarchically sparse signals and Kronecker product structured measurements arise naturally in a variety of applications. The simplest example of a hierarchical sparsity structure…