Dissertations / Theses on the topic 'Hauptkomponentenanalyse'
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Schmid, Martin. "Anwendung der Principal Component Analysis auf die Commodity-Preise." St. Gallen, 2007. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/02282663001/$FILE/02282663001.pdf.
Full textLu, Yun. "Risikoprämien von Unternehmensanleihen." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-125739.
Full textKhawaja, Antoun. "Automatic ECG analysis using principal component analysis and wavelet transformation." Karlsruhe Univ.-Verl. Karlsruhe, 2007. http://www.uvka.de/univerlag/volltexte/2007/227/.
Full textLücke-Janssen, Daniela. "Integration von Kern-Methoden in das medizinische Monitoring /." Düsseldorf : VDI-Verl, 2008. http://d-nb.info/991643704/04.
Full textAlexandris, Nikos [Verfasser], and Steffen [Akademischer Betreuer] Kuntz. "Burned area mapping via non-centered PCA using Public Domain Data and Free Open Source Software = Kartierung abgebrannter Flächen durch nicht-zentrierte Hauptkomponentenanalyse bei Benutzung von Public Domain Dateien und Free Open Source Software." Freiburg : Universität, 2011. http://d-nb.info/1123465053/34.
Full textAurich, Allan. "Modelle zur Beschreibung der Verkehrssicherheit innerörtlicher Hauptverkehrsstraßennetze unter besonderer Berücksichtigung der Umfeldnutzung." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-125311.
Full textA methodology is developed in order to predict the number of accidents within an urban main road network. The analysis was carried out by surveying the road network of Dresden. The resulting models allow the calculation of individual expectancy values for accidents with and without injury involving different traffic modes. The statistical modelling process is based on generalized linear models (GLM). These were chosen due to their ability to take into account certain non-normal distributions. In the specific case of accident counts, both the Poisson distribution and the negative binomial distribution are more suitable for reproducing the origination process than the normal distribution. Thus they were chosen as underlying distributions for the subsequent regressions. In order to differentiate overlaying influences, the main road network is separated into four basic elements: major intersections, road sections, minor intersections and approaches. Furthermore the major and minor intersections are additionally subdivided into signalised and non-signalised intersections. Separate models are calculated for different accident collectives for the various types of elements. Afterwards several methodologies for calculating aggregated network models are developed and analysed. Apart from traffic-related and infrastructural attributes, environmental parameters are derived taking into account the adjacent building structure as well as the surrounding land-use, and incorporated as explanatory variables within the regression. The environmental variables are derived from statistical analyses including correlation matrices, contingency tables and principal components analyses (PCA). As a result, a set of models is introduced which allows a multivariate calculation of expected accident counts for urban main road networks. The methodology developed can serve as a basis for a differentiated safety assessment of varying scenarios within a traffic planning process
Osunmadewa, Babatunde A., E. Csaplovics, A. Majdaldin R, D. Aralova, and C. O. Adeofun. "Regional assessment of trends in vegetation change dynamics using principal component analysis." SPIE, 2016. https://tud.qucosa.de/id/qucosa%3A35111.
Full textScholz, Matthias. "Approaches to analyse and interpret biological profile data." Phd thesis, [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980988799.
Full textRichter, Tom. "Einsatz der FT-IR-Mikrospektroskopie und multivariater Auswertealgorithmen zur Identifizierung und Klassifizierung von Tumorgeweben." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2002. http://nbn-resolving.de/urn:nbn:de:swb:14-1031654874828-52789.
Full textGalan, Roberto Fernandez. "Odor coding and memory traces in the antennal lobe of honeybee." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2003. http://dx.doi.org/10.18452/14997.
Full textTwo major novel results are reported in this work. The first concerns olfactory coding and the second concerns sensory memory. Both phenomena are investigated in the brain of the honeybee as a model system. Considering olfactory coding I demonstrate that the neural dynamics in the antennal lobe describe odor-specific trajectories during stimulation that converge to odor-specific attractors. The time interval to reach these attractors is, regardless of odor identity and concentration, approximately 800 ms. I show that support-vector machines and, in particular perceptrons provide a realistic and biological model of the interaction between the antennal lobe (coding network) and the mushroom body (decoding network). This model can also account for reaction-times of about 300 ms and for concentration invariance of odor perception. Regarding sensory memory I show that a single stimulation without reward induces changes of pairwise correlation between glomeruli in a Hebbian-like manner. I demonstrate that those changes of correlation suffice to retrieve the last stimulus presented in 2/3 of the bees studied. Succesful retrieval decays to 1/3 of the bees within the second minute after stimulation. In addition, a principal-component analysis of the spontaneous activity reveals that the dominant pattern of the network during the spontaneous activity after, but not before stimulation, reproduces the odor-induced activity pattern in 2/3 of the bees studied. One can therefore consider the odor-induced (changes of) correlation as traces of a short-term memory or as Hebbian reverberations.
Wedekind, Daniel, Alexander Trumpp, Frederik Gaetjen, Stefan Rasche, Klaus Matschke, Hagen Malberg, and Sebastian Zaunseder. "Assessment of blind source separation techniques for video-based cardiac pulse extraction." SPIE, 2017. https://tud.qucosa.de/id/qucosa%3A35267.
Full textAlouini, Olfa. "Country size, growth and the economic and monetary union." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2012. http://dx.doi.org/10.18452/16609.
Full textThe purpose of this dissertation is to investigate the relationship between country size and growth at the international level and comparatively in the Economic and Monetary Union, and to draw up its consequences for the conduct of growth-orientated fiscal policies. To further a global understanding of the link between country size and growth in the EMU, we follow an interdisciplinary approach, including macro-economic modelling (DSGE), econometrics and political economy analysis. Combining these analyses, we conclude that country size has an incidence on the economic structures of nations, the effects of their policies and therefore on their pace of growth. For this reason there is a need to reinstate the importance of country size and its consequences for the EMU.
Benko, Michal. "Functional data analysis with applications in finance." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2007. http://dx.doi.org/10.18452/15585.
Full textIn many different fields of applied statistics an object of interest is depending on some continuous parameter. Typical examples in finance are implied volatility functions, yield curves or risk-neutral densities. Due to the different market conventions and further technical reasons, these objects are observable only on a discrete grid, e.g. for a grid of strikes and maturities for which the trade has been settled at a given time-point. By collecting these functions for several time points (e.g. days) or for different underlyings, a bunch (sample) of functions is obtained - a functional data set. The first topic considered in this thesis concerns the strategies of recovering the functional objects (e.g. implied volatilities function) from the observed data based on the nonparametric smoothing methods. Besides the standard smoothing methods, a procedure based on a combination of nonparametric smoothing and the no-arbitrage-theory results is proposed for implied volatility smoothing. The second part of the thesis is devoted to the functional data analysis (FDA) and its connection to the problems present in the empirical analysis of the financial markets. The theoretical part of the thesis focuses on the functional principal components analysis -- functional counterpart of the well known multivariate dimension-reduction-technique. A comprehensive overview of the existing methods is given, an estimation method based on the dual problem as well as the two-sample inference based on the functional principal component analysis are discussed. The FDA techniques are applied to the analysis of the implied volatility and yield curve dynamics. In addition, the implementation of the FDA techniques together with a FDA library for the statistical environment XploRe are presented.
Tomowski, Daniel. "Kombiniert integrierte Veränderungsanalyse zur Schadenskartierung in urbanen Gebieten auf Basis sehr hoch auflösender multispektraler Bilddaten." Doctoral thesis, 2011. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-201107298216.
Full textBornschein, Jens. "Effiziente Einbringung von statistischem Formwissen in die Segmentierung von ATPase gefärbten Muskelfaserbildern." 2009. https://tud.qucosa.de/id/qucosa%3A70555.
Full textWagner, Silvia. "Identifizierung von Biomarkern mittels LC-MS-basiertem Metabonomics - Merkaptursäuren als Indikatoren für die Bildung toxischer Intermediate." Doctoral thesis, 2008. https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-35760.
Full textMetabonomics forms the end of the omics-cascade and represents a top-down strategy for the interpretation of the metabolome, i. e. all the low molecular weight metabolites in an intact organism. The aim of the approach is to analyse characteristic metabolite profiles by suitable untargeted screening methods in biological samples like urine or blood that can be obtained in a non-invasive manner. In the context of metabonomics, the term “metabotype” was defined according to the geno- and phenotype, respectively. Biostatistical methods based on pattern recognition techniques allow comparing metabolic signatures and extracting group specific metabolites and biomarkers. Therefore, metabonomics can be regarded as the fusion of bioanalytical and biostatistical techniques. Since its introduction in 1999, the concept of metabonomics has permanently gained importance in many fields of scientific research. One aim was to transfer the methodology, which was originally established to predict toxic effects in drug development processes, to human issues. Apart from preclinical questions, metabonomics is increasingly applied in the area of personalised medicine and nutrition. As the NMR technique used by pioneers of the field was too insensitive and the resulting metabolite profiles were too susceptible to biological and analytical confounders, more sensitive techniques like mass spectrometry were more and more applied. Especially mass spectrometry in combination with high performance liquid chromatography showed great promise for the screening of metabolites. However, after a very short time, it was clear that the data sets resulting from full scan/TOF-methods were too complex to “separate the wheat from the chaff” with chemometric procedures. Metabolite databases are still under construction, and therefore marker identification is challenging and requires complex analytical techniques. Thus, one strategy is to concentrate on a certain metabolite subset. The focus on a metabolite class with a close relation to the mechanism under investigation can considerably increase the prospects of success in the biomarker identification process. Due to a variety of exogenous and endogenous factors (drugs, industrial chemicals, food ingredients, and tobacco smoke) the human organism is steadily confronted with a multitude of electrophilic compounds. Oxidative damage of the DNA, proteins, and lipids is associated with the development of diseases like Parkinson’s, Alzheimer’s, cancer and widespread diseases like arteriosclerosis, allergies and coronary heart diseases. With the glutathione system the human organism is equipped with an efficient detoxification mechanism. The tripeptide glutathione reacts as nucleophile with exogenously and endogenously formed electrophilic intermediates. End products are mercapturic acids (N-acetyl-L-cysteine-adducts) and respective sulfoxides that are predominantly excreted with urine. Therefore, there is a close relationship between these mercapturic acid patterns and the electrophilic burden of an organism. In this context, the aim of this thesis was to develop a non-invasive human metabonomics approach that focuses the metabolite screening on the effect, dose and susceptibility marker class of the mercapturic acids. Thus, the prospects of success regarding the identification of potential biomarkers for various toxicological and pathological endpoints should be increased
Aurich, Allan. "Modelle zur Beschreibung der Verkehrssicherheit innerörtlicher Hauptverkehrsstraßennetze unter besonderer Berücksichtigung der Umfeldnutzung." Doctoral thesis, 2012. https://tud.qucosa.de/id/qucosa%3A27205.
Full textA methodology is developed in order to predict the number of accidents within an urban main road network. The analysis was carried out by surveying the road network of Dresden. The resulting models allow the calculation of individual expectancy values for accidents with and without injury involving different traffic modes. The statistical modelling process is based on generalized linear models (GLM). These were chosen due to their ability to take into account certain non-normal distributions. In the specific case of accident counts, both the Poisson distribution and the negative binomial distribution are more suitable for reproducing the origination process than the normal distribution. Thus they were chosen as underlying distributions for the subsequent regressions. In order to differentiate overlaying influences, the main road network is separated into four basic elements: major intersections, road sections, minor intersections and approaches. Furthermore the major and minor intersections are additionally subdivided into signalised and non-signalised intersections. Separate models are calculated for different accident collectives for the various types of elements. Afterwards several methodologies for calculating aggregated network models are developed and analysed. Apart from traffic-related and infrastructural attributes, environmental parameters are derived taking into account the adjacent building structure as well as the surrounding land-use, and incorporated as explanatory variables within the regression. The environmental variables are derived from statistical analyses including correlation matrices, contingency tables and principal components analyses (PCA). As a result, a set of models is introduced which allows a multivariate calculation of expected accident counts for urban main road networks. The methodology developed can serve as a basis for a differentiated safety assessment of varying scenarios within a traffic planning process.
Dodel, Silke. "Data driven analysis of brain activity and functional connectivity in fMRI." Doctoral thesis, 2002. http://hdl.handle.net/11858/00-1735-0000-0006-B562-D.
Full textKubitzki, Marcus. "Enhanced Conformational Sampling of Proteins Using TEE-REX." Doctoral thesis, 2007. http://hdl.handle.net/11858/00-1735-0000-000D-F123-4.
Full textSchnellen, Marina. "Analysis of Implied Volatility Surfaces." Doctoral thesis, 2007. http://hdl.handle.net/11858/00-1735-0000-000D-F225-7.
Full textGriesbach, Karoline. "Lane Change Prediction in the Urban Area." 2019. https://monarch.qucosa.de/id/qucosa%3A34546.
Full textFahrerassistenzsysteme und Algorithmen zum autonomen Fahren stellen ein aktuelles Forschungsfeld im Bereich der Fahrzeugentwicklung dar. Am Anfang wurden vor allem Fahrmanöver auf der Autobahn analysiert und vorhergesagt, mittlerweile hat sich das Forschungsfeld auch auf den urbanen Verkehr ausgeweitet. Fahrmanöver im urbanen Raum sind komplexer als Fahrmanöver auf Autobahnen und daher schwieriger vorherzusagen. Ziele für die Vorhersage von Fahrmanövern sind die Reduzierung von Verkehrsunfällen, die Verbesserung des Verkehrsflusses und die Entwicklung von zuverlässigen Algorithmen für das autonome Fahren. Um diese Ziele zu erreichen, wird das Fahrverhalten bei unterschiedlichen Fahrmanövern analysiert, wie z.B. beim Abbiegevorgang an Kreuzungen, bei der Notbremsung oder beim Spurwechsel. In dieser Arbeit wird der Spurwechsel im urbanen Straßenverkehr mit einem Echo State Network vorhergesagt. Zuerst wurden existierende Methoden zur Spurwechselvorhersage bezogen auf die Eingaben und die Ergebnisse bewertet, um danach die spurwechselbezogenen Variableneigenschaften bezüglich Spurwechsel- und Nicht-Spurwechselsequenzen zu analysieren. Die Daten, die Basis für diese ersten Untersuchungen waren, stammen aus einer Realfahrstudie. Basierend auf diesen Resultaten wurden die finalen Variablen (Lenkwinkel, Blinker und Blickrichtung) für weitere Berechnungen ausgewählt. Mit den Daten aus der Realfahrstudie und den finalen Variablen wurden die Parameter des Echo State Networks optimiert und letztendlich wurden linke und rechte Spurwechsel vorhergesagt. Zusätzlich wurde das Echo State Network mit einem vorwärtsgerichteten neuronalen Netz verglichen. Das Echo State Network konnte linke und rechte Spurwechsel erfolgreicher vorhersagen als das vorwärtsgerichtete neuronale Netz.