DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Robuste Schätzung durch Approximation von Matrizen niedrigen Ranges

Zeitlhöfer, Julian (2016) Robuste Schätzung durch Approximation von Matrizen niedrigen Ranges. Bachelor's, Technical University of Munich.

Full text not available from this repository.


In this thesis is discussed whether the theory of low rank decomposition (LRD) can be used for creating robust estimators. Therefore, robust location estimation and robust covariance estimation is used. In a first section particular frame conditions for each experiment are set up for creating a synthetic data matrix. The output of decomposing this matrix is a low ranked matrix free from errors and a sparse error matrix containing all detected errors. By analyzing those two matrices a weighting factor can be determined. Aspects are robustness, the quality of location and covariance estimation and a high accuracy at detecting outliers. An appropriate and well-fitting weighting factor is used in a second block of experiments. Low rank decomposition is compared to other estimators such as robust minimum covariance determinant (MCD) and the arithmetic mean. Good results at using the low rank decomposition are achieved when choosing an appropriate weighting factor and with good information about the given data. Nevertheless, is it very important to keep in mind that the weighting factor can have a very big influence on the parameter estimation.

Item URL in elib:https://elib.dlr.de/108461/
Document Type:Thesis (Bachelor's)
Title:Robuste Schätzung durch Approximation von Matrizen niedrigen Ranges
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:50
Keywords:low rank decomposition, minimum covariance determinant, robust estimation
Institution:Technical University of Munich
Department:Signal Processing in Earth Observation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - SAR-Methodology
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Wang, Yuanyuan
Deposited On:29 Nov 2016 16:01
Last Modified:29 Nov 2016 16:01

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.