Multi-Time Wideband LASSO; An Optimization Approach for Paleoclimatology Data
(2021) In Master's thesis in Mathematical Scieces FMSM01 20202Mathematical Statistics
- Abstract
- In this work, a new method for spectral analysis of irregularly sampled data from paleoclimatology is proposed. The spectral estimate is formulated as an inverse problem and extracts information from multiple cores sampled at different times with different phases, while being robust to errors in the assumed sampling times. The proposed method is also shown to attain the misspecified Cramér-Rao lower bound when the $SNR$ is sufficiently high and the performance is compared to other commonly used spectral estimation techniques in the field using simulated data, it is then tested on real world data.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9059625
- author
- Svedberg, David LU
- supervisor
- organization
- course
- FMSM01 20202
- year
- 2021
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Signal Processing, Variance Bounds, Convex Optimization, LASSO, Irregular Sampling, Paleoclimatology
- publication/series
- Master's thesis in Mathematical Scieces
- report number
- LUTFMS-3423-2021
- ISSN
- 1404-6342
- other publication id
- 2021:E46
- language
- English
- id
- 9059625
- date added to LUP
- 2021-07-05 14:51:50
- date last changed
- 2021-08-20 16:53:49
@misc{9059625, abstract = {{In this work, a new method for spectral analysis of irregularly sampled data from paleoclimatology is proposed. The spectral estimate is formulated as an inverse problem and extracts information from multiple cores sampled at different times with different phases, while being robust to errors in the assumed sampling times. The proposed method is also shown to attain the misspecified Cramér-Rao lower bound when the $SNR$ is sufficiently high and the performance is compared to other commonly used spectral estimation techniques in the field using simulated data, it is then tested on real world data.}}, author = {{Svedberg, David}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's thesis in Mathematical Scieces}}, title = {{Multi-Time Wideband LASSO; An Optimization Approach for Paleoclimatology Data}}, year = {{2021}}, }