DFG Schwerpunktprogramm 1798: Compressed Sensing in der Informationsverarbeitung

Nutzung von Struktur im Compressed Sensing durch Nebenbedingungen (EXPRESS)

Compressed sensing is a signal processing technique for efficient acquisition and reconstruction of signals based on an underlying model sparsity, which allows to recover the signal of interest from far fewer samples than required by traditional acquisition systems operating at Nyquist rate. In EXPRESS I, we have investigated the impact of side constraints on the measurement system and the signal representation. In particular, we have considered sparse reconstruction techniques for multidimensional frequency estimation and studied how structure in conventional sensing systems or sensor arrays, the source signal of interest, and the temporal variation in multi snapshot scenarios can be exploited to improve reconstruction guarantees and estimation performance. While the focus of EXPRESS I was on the analysis of sparse signals under various types of structure, the focus of EXPRESS II (Exploiting structure in compressed sensing using side constraints: From analysis to system design – Funding phase II) will shift towards the design of analog-digital acquisition systems for multidimensional frequency estimation under various types of structure.


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Frühere Mitarbeiter: Tobias Fischer, Andreas Tillmann