TR2020-052
Robust Parameter Estimation of Contaminated Damped Exponentials
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- "Robust Parameter Estimation of Contaminated Damped Exponentials", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053507, April 2020, pp. 5500-5504.BibTeX TR2020-052 PDF Video
- @inproceedings{Xie2020apr,
- author = {Xie, Youye and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T.},
- title = {Robust Parameter Estimation of Contaminated Damped Exponentials},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2020,
- pages = {5500--5504},
- month = apr,
- publisher = {IEEE},
- doi = {10.1109/ICASSP40776.2020.9053507},
- issn = {2379-190X},
- isbn = {978-1-5090-6631-5},
- url = {https://www.merl.com/publications/TR2020-052}
- }
,
- "Robust Parameter Estimation of Contaminated Damped Exponentials", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053507, April 2020, pp. 5500-5504.
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MERL Contacts:
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Research Areas:
Abstract:
Parameter estimation of damped exponential signals has wide applications including fault detection and system parameter identification, etc. However, existing methods for estimating parameters of damped exponentials are either sensitive to noise or restricted to dealing with a certain type of noise such as Gaussian noise. In this paper we aim to estimate parameters of damped exponentials from contaminated signal, i.e., a mixture of damped exponentials, random Gaussian noise, and spike interference. We propose two robust approaches, a convex one solved by the alternating direction method of multipliers (ADMM) and a non-convex one solved by coordinate descent, to recovering a low-rank Hankel matrix of damped exponentials from noisy measurements for further parameter estimation using the matrix pencil technique. Numerical experiments show that our proposed methods outperform classical ones in detecting small damped fault signatures from noisy measurements. While the convex approach is amenable to theoretical analysis and global convergence guarantees, the non-convex one exhibits more robustness and computational efficiency
Related News & Events
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NEWS MERL presenting 13 papers and an industry talk at ICASSP 2020 Date: May 4, 2020 - May 8, 2020
Where: Virtual Barcelona
MERL Contacts: Petros T. Boufounos; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & AudioBrief- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.
This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.