Shutin, Dmitriy and Wang, Wei and Jost, Thomas (2013) Incremental Sparse Bayesian Learning for Parameter Estimation of Superimposed Signals. In: 2015 International Conference on Sampling Theory and Applications, SampTA 2015. 10th International Conference on Sampling Theory and Applications, 2013-07-01 - 2013-07-05, Bremen, Deutschland.
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Abstract
This work discuses a novel algorithm for joint sparse estimation of superimposed signals and their parameters. The proposed method is based on two concepts: a variational Bayesian version of the incremental sparse Bayesian learning (SBL)- fast variational SBL - and a variational Bayesian approach for parameter estimation of superimposed signal models. Both schemes estimate the unknown parameters by minimizing the variational lower bound on model evidence; also, these optimizations are performed incrementally with respect to the parameters of a single component. It is demonstrated that these estimations can be naturally unified under the framework of variational Bayesian inference. It allows, on the one hand, for an adaptive dictionary design for FV-SBL schemes, and, on the other hand, for a fast superresolution approach for parameter estimation of superimposed signals. The experimental evidence collected with synthetic data as well as with estimation results for measured multipath channels demonstrate the effectiveness of the proposed algorithm.
Item URL in elib: | https://elib.dlr.de/82752/ | ||||||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||
Title: | Incremental Sparse Bayesian Learning for Parameter Estimation of Superimposed Signals | ||||||||||||||||
Authors: |
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Date: | 2013 | ||||||||||||||||
Journal or Publication Title: | 2015 International Conference on Sampling Theory and Applications, SampTA 2015 | ||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||
Open Access: | No | ||||||||||||||||
Gold Open Access: | No | ||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||
Status: | Published | ||||||||||||||||
Keywords: | Multipath estimation, Sparse Bayesian learning | ||||||||||||||||
Event Title: | 10th International Conference on Sampling Theory and Applications | ||||||||||||||||
Event Location: | Bremen, Deutschland | ||||||||||||||||
Event Type: | international Conference | ||||||||||||||||
Event Start Date: | 1 July 2013 | ||||||||||||||||
Event End Date: | 5 July 2013 | ||||||||||||||||
Organizer: | Jacobs University Bremen | ||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||
HGF - Program: | Aeronautics | ||||||||||||||||
HGF - Program Themes: | ATM and Operation (old) | ||||||||||||||||
DLR - Research area: | Aeronautics | ||||||||||||||||
DLR - Program: | L AO - Air Traffic Management and Operation | ||||||||||||||||
DLR - Research theme (Project): | L - Communication, Navigation and Surveillance (old) | ||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||
Institutes and Institutions: | Institute of Communication and Navigation > Communications Systems | ||||||||||||||||
Deposited By: | Shutin, Dmitriy | ||||||||||||||||
Deposited On: | 18 Sep 2013 09:45 | ||||||||||||||||
Last Modified: | 24 Apr 2024 19:49 |
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