Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
O. Musa, P. Jung, N. Görtz:
"Generalized Approximate Message Passing for Unlimited Sampling of Sparse Signals";
Poster: Proceedings IEEE Global Conference on Signal and Information Processing,
Anaheim, California, USA;
26.11.2018
- 29.11.2018; in: "Proceedings IEEE Global Conference on Signal and Information Processing",
IEEE,
(2018),
S. 336
- 340.
Kurzfassung deutsch:
In this paper we consider the generalized approxi-
mate message passing (GAMP) algorithm for recovering a sparse
signal from modulo samples of randomized projections of the
unknown signal. The modulo samples are obtained by a self-reset
(SR) analog to digital converter (ADC). Additionally, in contrast
to previous work on SR ADC, we consider a scenario where
the compressed sensing (CS) measurements (i.e., randomized
projections) are sent through a communication channel, namely
an additive white Gaussian noise (AWGN) channel before being
quantized by a SR ADC. To show the effectiveness of the proposed
approach, we conduct Monte-Carlo (MC) simulations for both
noiseless and noisy case. The results show strong ability of the
proposed algorithm to fight the nonlinearity of the SR ADC,
as well as the possible additional distortion introduced by the
AWGN channel.
Kurzfassung englisch:
In this paper we consider the generalized approxi-
mate message passing (GAMP) algorithm for recovering a sparse
signal from modulo samples of randomized projections of the
unknown signal. The modulo samples are obtained by a self-reset
(SR) analog to digital converter (ADC). Additionally, in contrast
to previous work on SR ADC, we consider a scenario where
the compressed sensing (CS) measurements (i.e., randomized
projections) are sent through a communication channel, namely
an additive white Gaussian noise (AWGN) channel before being
quantized by a SR ADC. To show the effectiveness of the proposed
approach, we conduct Monte-Carlo (MC) simulations for both
noiseless and noisy case. The results show strong ability of the
proposed algorithm to fight the nonlinearity of the SR ADC,
as well as the possible additional distortion introduced by the
AWGN channel.
Schlagworte:
Generalized approximate message passing, self- reset analog to digital converter, noisy channel, compressed sensing, Bernoulli-Gaussian mixture
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/GlobalSIP.2018.8646332
Elektronische Version der Publikation:
https://publik.tuwien.ac.at/files/publik_274257.pdf
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.