Tesis sobre el tema "Non-stationary distribution"
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Hesarkazzazi, Sina. "Stationary vs. non-stationary modeling of flood frequency distribution across North West England (UK)". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Buscar texto completoRajagopalan, Satish. "Detection of Rotor and Load Faults in BLDC Motors Operating Under Stationary and Non-Stationary Conditions". Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/11524.
Texto completoMuševič, Sašo. "Non-stationary sinusoidal analysis". Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/123809.
Texto completoMany types of everyday signals fall into the non-stationary sinusoids category. A large family of such signals represent audio, including acoustic/electronic, pitched/transient instrument sounds, human speech/singing voice, and a mixture of all: music. Analysis of such signals has been in the focus of the research community for decades. The main reason for such intense focus is the wide applicability of the research achievements to medical, financial and optical applications, as well as radar/sonar signal processing and system analysis. Accurate estimation of sinusoidal parameters is one of the most common digital signal processing tasks and thus represents an indispensable building block of a wide variety of applications. Classic time-frequency transformations are appropriate only for signals with slowly varying amplitude and frequency content - an assumption often violated in practice. In such cases, reduced readability and the presence of artefacts represent a significant problem. Time and frequency resolu
Mamikonyan, Arsen. "Variational inference for non-stationary distributions". Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113125.
Texto completoThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 49).
In this thesis, I look at multiple Variational Inference algorithm, transform Kalman Variational Bayes and Stochastic Variational Inference into streaming algorithms and try to identify if any of them work with non-stationary distributions. I conclude that Kalman Variational Bayes can do as good as any other algorithm for stationary distributions, and tracks non-stationary distributions better than any other algorithm in question.
by Arsen Mamikonyan.
M. Eng.
Jalbert, Jonathan. "Développement d'un modèle statistique non stationnaire et régional pour les précipitations extrêmes simulées par un modèle numérique de climat". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAU032/document.
Texto completoPrecipitation extremes plays a major role in flooding events and their occurrence as well as their intensity are expected to increase. It is therefore important to anticipate the impacts of such an increase to ensure the public safety and the infrastructure sustainability. Since climate models are the only tools for providing quantitative projections of precipitation, flood risk management for the future climate may be based on their simulations. Most of the time, the Extreme value theory is used to estimate the extreme precipitations from a climate simulation, such as the T-year return levels. The variance of the estimations are generally large notably because the sample size of the maxima series are short. Such variance could have a significant impact for flood risk management. It is therefore relevant to reduce the estimation variance of simulated return levels. For this purpose, the aim of this paper is to develop a non-stationary and regional statistical model especially suited for climate models that estimates precipitation extremes. At first, the non-stationarity is removed by a preprocessing approach. Thereafter, the spatial correlation is modeled by a Bayesian hierarchical model including an intrinsic Gaussian Markov random field. The model has been used to estimate the 100-year return levels over North America from a simulation by the Canadian Regional Climate Model. The results show a large estimation variance reduction when using the regional model
Hili, Ouagnina. "Contribution à l'estimation des modèles de séries temporelles non linéaires". Université Louis Pasteur (Strasbourg) (1971-2008), 1995. http://www.theses.fr/1995STR13169.
Texto completoNguyen, Yen Thi Hong. "Time-frequency distributions : approaches for incomplete non-stationary signals". Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/19681/.
Texto completoKinnally, Michael Sean. "Stationary distributions for stochastic delay differential equations with non-negativity constraints". Diss., [La Jolla] : University of California, San Diego, 2009. http://wwwlib.umi.com/cr/ucsd/fullcit?p3355747.
Texto completoTitle from first page of PDF file (viewed June 23, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 114-116).
Fossi, Fotsi Yannick. "Dynamique morpho-sédimentaire de l’estuaire du Wouri, Cameroun". Thesis, La Rochelle, 2022. http://www.theses.fr/2022LAROS012.
Texto completoThe Wouri estuary, located in the heart of the Gulf of Guinea and open to the Atlantic Ocean, is subject to a wide range of atmospheric, oceanic, continental and anthropic influences at different time scales (short and long term) controlling its evolution. The first part of this thesis, based on archives dating back to the 20th century, allows us to reconstruct the history of the evolution of the Wouri estuary coastline. At the same time, in order to determine the evolution trends of the water levels, to quantify and qualify the kinematics of the coastline and the bottoms in the estuary, an inventory, digitization and analysis of historical documents was carried out. This allowed to record an evolution of the average level at a rate of about 25mm/year in 17 years (2002 - 2019). The results revealed a predominance of variations dominated by erosion downstream and conversely by accretion upstream, over the 64-year period (1948-2012). These trends are accentuated by the presence of amplifying factors (anthropogenic pressure and climate change). In order to study the hydrodynamic and sedimentary processes in the short term, a numerical modeling of the tidal propagation and the distribution of salinities and fine sediments was performed using TELEMAC 3D (calibrated and validated thanks to in-situ measurements acquired during 2019). The tide showed an asymmetry dominated by the ebb in its lower part and inversely by the flood in its upper part. The distribution of salinity allowed to characterize the estuary from well mixed in spring tide, particularly in low water to stratified in neap tide, particularly in flood period. Seasonal variations of the river regime have shown a longitudinal migration of the position of the maximum turbidity zone : upstream during low water and downstream during high water with a massive export of sediments in the intermediate and downstream part of the estuary. In a current context of climate change associated with strong anthropogenic impacts, this study highlights the need to use historical archives, in-situ data coupled with a numerical model to better understand the past and present evolution of hydrodynamics and sediment dynamics
RANDAZZO, VINCENZO. "Novel neural approaches to data topology analysis and telemedicine". Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2850610.
Texto completoUndin, Torgny. "Development and improvement of methods for characterization of HPLC stationary phases". Licentiate thesis, Uppsala universitet, Analytisk kemi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-166978.
Texto completoProcházka, Petr. "Využití zobecněných funkcí v mechanice kontinua". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-392850.
Texto completoAyari, Samia. "Nonparametric estimation of the dependence function for multivariate extreme value distributions". Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4078.
Texto completoIn this thesis, we investigate the nonparametric estimation of the dependence function for multivariate extreme value distributions. Firstly, we assume independent and identically distributed random variables (i.i.d). Several nonparametric estimators are compared for a trivariate dependence function of logistic type in two different cases. In a first analysis, we suppose that marginal functions are generalized extreme value distributions. In a second investigation, we substitute the marginal function by the empirical distribution function. Monte Carlo simulations show that the Gudendorf-Segers (Gudendorf and Segers, 2011) estimator outperforms the other estimators for different sample sizes. Secondly, we drop the i.i.d assumption as it’s not verified in time series analysis. Considering the univariate framework, we examine the extremal behavior of a stationary Gaussian autoregressive process. In the multivariate setting, we prove the asymptotic consistency of the Pickands dependence function estimator. This theoretical finding is confirmed by empirical investigations in the asymptotic independence case as well as the asymptotic dependence case. Finally, the Gudendorf-Segers estimator is used to model the dependence structure of extreme ozone concentrations in locations that record several exceedances for both guideline and limit values of the Tunisian air quality standard NT.106.04
Hussain, Zahir M. "Adaptive instantaneous frequency estimation: Techniques and algorithms". Thesis, Queensland University of Technology, 2002. https://eprints.qut.edu.au/36137/7/36137_Digitised%20Thesis.pdf.
Texto completoPilloni, Giovanni [Verfasser]. "Distribution and dynamics of contaminant degraders and microbial communities in stationary and non-stationary contaminant plumes / Giovanni Pilloni". 2011. http://d-nb.info/1011394111/34.
Texto completoMuscolino, G. y Alessandro Palmeri. "Peak response of non-linear oscillators under stationary white noise". 2007. http://hdl.handle.net/10454/601.
Texto completoDas, Soumya. "Stationary and Cyclostationary Processes for Time Series and Spatio-Temporal Data". Diss., 2021. http://hdl.handle.net/10754/670097.
Texto completoVarma, Vishal V. "Robust Framework for System Architecture and Hand-offs in Wireless and Cellular Communication Systems". 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-85.
Texto completoMusselman, Marcus William. "Monitoring of biomedical systems using non-stationary signal analysis". 2013. http://hdl.handle.net/2152/23248.
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"Stationary distributions for stochastic delay differential equations with non-negativity constraints". UNIVERSITY OF CALIFORNIA, SAN DIEGO, 2009. http://pqdtopen.proquest.com/#viewpdf?dispub=3355747.
Texto completoΠουλημένος, Άγγελος. "Μοντελοποίηση μη-στάσιμων ταλαντώσεων μέσω συναρτησιακών μοντέλων TARMA: μέθοδοι εκτίμησης και ιδιότητες αυτών". Thesis, 2007. http://nemertes.lis.upatras.gr/jspui/handle/10889/766.
Texto completoThe thesis studies the problem of non-stationary random vibration modeling and analysis based on available measurements of the vibration signal via Functional Series Time-dependent AutoRegressive / AutoRegressive Moving Average (FS-TAR/ TARMA) models. The aims of the thesis include the assessment of the applicability of FS-TAR/TARMA methods for the modeling and analysis of non-stationary random vibration, as well as their comparison with alternative time-domain parametric methods. In addition, significant attention has been paid to the FS-TAR/TARMA estimation problem and to the theoretical asymptotic analysis of the estimators. A critical overview and comparison of time-domain, parametric, non-stationary random vibration modeling and analysis methods is firstly presented, where the high potential of FS-TAR/TARMA methods is demonstrated. In the following, a number of issues concerning the FS-TAR/TARMA model (parameter) estimation and model structure selection are considered. The effectiveness of the FS-TARMA methods for non-stationary random vibration modeling and analysis is experimentally demonstrated, through their application for the recovery of the dynamical characteristics of a time-varying bridge-like laboratory structure. In the sequel, the thesis focuses on the asymptotic analysis of “general” (that is not necessarily periodically evolving) FS-TAR/TARMA estimators. In particular, the Weighted Least Squares (WLS) and Maximum Likelihood (ML) estimators are both investigated, while a Multi Stage (MS) estimator, that approximates the ML estimator at reduced complexity, is developed. The consistency of the considered estimators is established and their asymptotic distribution is extracted. Furthermore, a consistent estimator of the asymptotic covariance matrix is formulated and an FS-TAR/TARMA model validation method is proposed. The validity of the theoretical asymptotic analysis results is assessed through several Monte Carlo studies.
Machuca-Mory, David Francisco. "Geostatistics with location-dependent statistics". Phd thesis, 2010. http://hdl.handle.net/10048/1275.
Texto completoMining Engineering