Search results for "Spline"
showing 10 items of 170 documents
Implementation and experimental validation of a real-time PWM algorithm based on B-Spline carriers for three phase voltage source inverters
2009
This paper presents the implementation and experimental results of an algebraic real-time sinusoidal pulse width modulation algorithm (SPWM) based on B-Spline carriers. B-spline functions are used as carrier signals with the aim to to reduce harmonic content of the three phase inverter output voltage. The presented algorithm eliminates the problem of B-spline recursive evaluation with convolution integrals or convolution sums in digital counterpart. The pulse pattern synthesis is made with the help pre-calculated duty cycle expressions. In this way there is no real need to synthesize the carrier signal so the hardware and the whole inverter control system becomes cheaper, more reliable and …
Approximation properties of higher degree F-transforms based on B-splines
2015
The paper deals with the F-transform with polynomial components with respect to a generalized fuzzy partition given by B-splines. We investigate approximation properties of the inverse F-transform in this case and prove that using B-splines allows us to improve the quality of approximation of smooth functions.
B-Spline Estimation in a Survey Sampling Framework
2021
Nonparametric regression models have been used more and more over the last years to model survey data and incorporate efficiently auxiliary information in order to improve the estimation of totals, means or other study parameters such as Gini index or poverty rate. B-spline nonparametric regression has the benefit of being very flexible in modeling nonlinear survey data while keeping many similarities and properties of the classical linear regression. This method proved to be efficient for deriving a unique system of weights which allowed to estimate in an efficient way and simultaneously many study parameters. Applications on real and simulated survey data showed its high efficiency. This …
Long gaps in multivariate spatio-temporal data: an approach based on functional data analysis
2015
The main aim of this paper is to perform Functional Principal Component Analysis (FPCA) taking into account spatio-temporal correlation structures, in order to fill in missing values in spatio-temporal multivariate data set. A spatial and a spatio-temporal variant of the classical temporal FPCA is considered; in other words, FPCA is carried out after modeling data with respect to more than one dimension: space (long, lat) or space+time. Moreover, multidimensional FPCA is extended to multivariate context (more than one variable). Information on spatial or spatiotemporal structures are efficiently extracted by applying Generalized Additive Models (GAMs). Both simulation studies and some perfo…
Functional linear regression with functional rensponse application to prediction of electricity consumption
2008
Functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. The slope function is estimated with a tensor product splines. Some computational issues are addressed by means of a simulation study. This model serves to analyze a real data set concerning electricity consumption in Sardinia. The interest lies in predicting either incoming weekend or incoming weekdays consumption curves if actual weekdays consumption is known.
Comparing Spatial and Spatio-temporal FPCA to Impute Large Continuous Gaps in Space
2018
Multivariate spatio-temporal data analysis methods usually assume fairly complete data, while a number of gaps often occur along time or in space. In air quality data long gaps may be due to instrument malfunctions; moreover, not all the pollutants of interest are measured in all the monitoring stations of a network. In literature, many statistical methods have been proposed for imputing short sequences of missing values, but most of them are not valid when the fraction of missing values is high. Furthermore, the limitation of the methods commonly used consists in exploiting temporal only, or spatial only, correlation of the data. The objective of this paper is to provide an approach based …
Comparing FPCA Based on Conditional Quantile Functions and FPCA Based on Conditional Mean Function
2019
In this work functional principal component analysis (FPCA) based on quantile functions is proposed as an alternative to the classical approach, based on the functional mean. Quantile regression characterizes the conditional distribution of a response variable and, in particular, some features like the tails behavior; smoothing splines have also been usefully applied to quantile regression to allow for a more flexible modelling. This framework finds application in contexts involving multiple high frequency time series, for which the functional data analysis (FDA) approach is a natural choice. Quantile regression is then extended to the estimation of functional quantiles and our proposal exp…
Functional principal component analysis for multivariate multidimensional environmental data
2015
Data with spatio-temporal structure can arise in many contexts, therefore a considerable interest in modelling these data has been generated, but the complexity of spatio-temporal models, together with the size of the dataset, results in a challenging task. The modelization is even more complex in presence of multivariate data. Since some modelling problems are more natural to think through in functional terms, even if only a finite number of observations is available, treating the data as functional can be useful (Berrendero et al. in Comput Stat Data Anal 55:2619–2634, 2011). Although in Ramsay and Silverman (Functional data analysis, 2nd edn. Springer, New York, 2005) the case of multiva…
Modelling Spatio-Temporal Elephant Movement Data: a Generalized Additive Mixed Models Framework
2014
This thesis focuses on understanding how environmental factors influence elephant movement and in investigating the spatio-temporal patterns. The thesis analyses movement data of some African elephants (Loxodonta Africana) living in the Kruger National Park and its associated private reserves of South Africa. Due to heterogeneity among elephants, and nonlinear relationships between elephant movement and environmental variables, Generalized Additive Mixed Models (GAMMs) were employed. Results showed delayed effects of rainfall and temperature and particular trends in time and space.
Blood vessel segmentation and width estimation in ultra-wide field scanning laser ophthalmoscopy.
2014
Features of the retinal vasculature, such as vessel widths, are considered biomarkers for systemic disease. The aim of this work is to present a supervised approach to vessel segmentation in ultra-wide field of view scanning laser ophthalmoscope (UWFoV SLO) images and to evaluate its performance in terms of segmentation and vessel width estimation accuracy. The results of the proposed method are compared with ground truth measurements from human observers and with existing state-of-the-art techniques developed for fundus camera images that we optimized for UWFoV SLO images. Our algorithm is based on multi-scale matched filters, a neural network classifier and hysteresis thresholding. After …