965 resultados para nonlinear least-square fit
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Currently, the standards that deal with the determination of the properties of rigidity and strength for structural round timber elements do not take in consideration in their calculations and mathematical models the influence of the existing irregularities in the geometry of these elements. This study has as objective to determine the effective value of the modulus of longitudinal elasticity for structural round timber pieces of the Eucalyptus citriodora genus by a technique of optimization allied to the Inverse Analysis Method, to the Finite Element Method and the Least Square Method.
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Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional least-square method (LS). Among these the most important are: there are no restrictions on linearity or in the form which the parameters appears in the mathematical model describing the system, and it is not required that these parameters be time invariant. The EKF uses the statistical properties of the process and the observation noise, to produce estimates based on the mean square error of the estimates themselves. Differently, the LS minimizes a cost function based on the plant output behavior. Results for the estimation of some longitudinal aerodynamic derivatives from simulated data are presented.
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The accuracy of modelling of rotor systems composed of rotors, oil film bearings and a flexible foundation, is evaluated and discussed in this paper. The model validation of different models has been done by comparing experimental results with numerical results by means. The experimental data have been obtained with a fully instrumented four oil film bearing, two shafts test rig. The fault models are then used in the frame of a model based malfunction identification procedure, based on a least square fitting approach applied in the frequency domain. The capability of distinguishing different malfunctions has been investigated, even if they can create similar effects (such as unbalance, rotor bow, coupling misalignment and others) from shaft vibrations measured in correspondence of the bearings.
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In the present work we describe a method which allows the incorporation of surface tension into the GENSMAC2D code. This is achieved on two scales. First on the scale of a cell, the surface tension effects are incorporated into the free surface boundary conditions through the computation of the capillary pressure. The required curvature is estimated by fitting a least square circle to the free surface using the tracking particles in the cell and in its close neighbors. On a sub-cell scale, short wavelength perturbations are filtered out using a local 4-point stencil which is mass conservative. An efficient implementation is obtained through a dual representation of the cell data, using both a matrix representation, for ease at identifying neighbouring cells, and also a tree data structure, which permits the representation of specific groups of cells with additional information pertaining to that group. The resulting code is shown to be robust, and to produce accurate results when compared with exact solutions of selected fluid dynamic problems involving surface tension.
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Prediction of variety composite means was shown to be feasible without diallel crossing the parental varieties. Thus, the predicted mean for a quantitative trait of a composite is given by: Yk = a1 sigmaVj + a2sigmaTj + a3 - a4
, with coefficients a1 = (n - 2k)/k²(n - 2); a2 = 2n(k - 1)/k²(n - 2); a3 = n(k - 1)/k(n - 1)(n - 2); and a4 = n²(k - 1)/k(n - 1)(n - 2); summation is for j = 1 to k, where k is the size of the composite (number of parental varieties of a particular composite) and n is the total number of parent varieties. Vj is the mean of varieties and Tj is the mean of topcrosses (pool of varieties as tester), and
and
are the respective average values in the whole set. Yield data from a 7 x 7 variety diallel cross were used for the variety means and for the "simulated" topcross means to illustrate the proposed procedure. The proposed prediction procedure was as effective as the prediction based on Yk =
- (
-
)/k, where
and
refer to the mean of hybrids (F1) and parental varieties, respectively, in a variety diallel cross. It was also shown in the analysis of variance that the total sum of squares due to treatments (varieties and topcrosses) can be orthogonally partitioned following the reduced model Yjj = mu + ½(v j + v j) +
+ h j+ h j, thus making possible an F test for varieties, average heterosis and variety heterosis. Least square estimates of these effects are also given
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. The influence of vine water status was studied in commercial vineyard blocks of Vilis vinifera L. cv. Cabernet Franc in Niagara Peninsula, Ontario from 2005 to 2007. Vine performance, fruit composition and vine size of non-irrigated grapevines were compared within ten vineyard blocks containing different soil and vine water status. Results showed that within each vineyard block water status zones could be identified on GIS-generated maps using leaf water potential and soil moisture measurements. Some yield and fruit composition variables correlated with the intensity of vine water status. Chemical and descriptive sensory analysis was performed on nine (2005) and eight (2006) pairs of experimental wines to illustrate differences between wines made from high and low water status winegrapes at each vineyard block. Twelve trained judges evaluated six aroma and flavor (red fruit, black cherry, black current, black pepper, bell pepper, and green bean), thr~e mouthfeel (astringency, bitterness and acidity) sensory attributes as well as color intensity. Each pair of high and low water status wine was compared using t-test. In 2005, low water status (L WS) wines from Buis, Harbour Estate, Henry of Pelham (HOP), and Vieni had higher color intensity; those form Chateau des Charmes (CDC) had high black cherry flavor; those at RiefEstates were high in red fruit flavor and at those from George site was high in red fruit aroma. In 2006, low water status (L WS) wines from George, Cave Spring and Morrison sites were high in color intensity. L WS wines from CDC, George and Morrison were more intense in black cherry aroma; LWS wines from Hernder site were high in red fruit aroma and flavor. No significant differences were found from one year to the next between the wines produced from the same vineyard, indicating that the attributes of these wines were maintained almost constant despite markedly different conditions in 2005 and 2006 vintages. Partial ii Least Square (PLS) analysis showed that leaf \}' was associated with red fruit aroma and flavor, berry and wine color intensity, total phenols, Brix and anthocyanins while soil moisture was explained with acidity, green bean aroma and flavor as well as bell pepper aroma and flavor. In another study chemical and descriptive sensory analysis was conducted on nine (2005) and eight (2006) medium water status (MWS) experimental wines to illustrate differences that might support the sub-appellation system in Niagara. The judges evaluated the same aroma, flavor, and mouthfeel sensory attributes as well as color intensity. Data were analyzed using analysis of variance (ANOVA), principal component analysis (PCA) and discriminate analysis (DA). ANOV A of sensory data showed regional differences for all sensory attributes. In 2005, wines from CDC, HOP, and Hemder sites showed highest. r ed fruit aroma and flavor. Lakeshore and Niagara River sites (Harbour, Reif, George, and Buis) wines showed higher bell pepper and green bean aroma and flavor due to proximity to the large bodies of water and less heat unit accumulation. In 2006, all sensory attributes except black pepper aroma were different. PCA revealed that wines from HOP and CDC sites were higher in red fruit, black currant and black cherry aroma and flavor as well as black pepper flavor, while wines from Hemder, Morrison and George sites were high in green bean aroma and flavor. ANOV A of chemical data in 2005 indicated that hue, color intensity, and titratable acidity (TA) were different across the sites, while in 2006, hue, color intensity and ethanol were different across the sites. These data indicate that there is the likelihood of substantial chemical and sensory differences between clusters of sub-appellations within the Niagara Peninsula iii
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La modélisation géométrique est importante autant en infographie qu'en ingénierie. Notre capacité à représenter l'information géométrique fixe les limites et la facilité avec laquelle on manipule les objets 3D. Une de ces représentations géométriques est le maillage volumique, formé de polyèdres assemblés de sorte à approcher une forme désirée. Certaines applications, tels que le placage de textures et le remaillage, ont avantage à déformer le maillage vers un domaine plus régulier pour faciliter le traitement. On dit qu'une déformation est \emph{quasi-conforme} si elle borne la distorsion. Cette thèse porte sur l’étude et le développement d'algorithmes de déformation quasi-conforme de maillages volumiques. Nous étudions ces types de déformations parce qu’elles offrent de bonnes propriétés de préservation de l’aspect local d’un solide et qu’elles ont été peu étudiées dans le contexte de l’informatique graphique, contrairement à leurs pendants 2D. Cette recherche tente de généraliser aux volumes des concepts bien maitrisés pour la déformation de surfaces. Premièrement, nous présentons une approche linéaire de la quasi-conformité. Nous développons une méthode déformant l’objet vers son domaine paramétrique par une méthode des moindres carrés linéaires. Cette méthode est simple d'implémentation et rapide d'exécution, mais n'est qu'une approximation de la quasi-conformité car elle ne borne pas la distorsion. Deuxièmement, nous remédions à ce problème par une approche non linéaire basée sur les positions des sommets. Nous développons une technique déformant le domaine paramétrique vers le solide par une méthode des moindres carrés non linéaires. La non-linéarité permet l’inclusion de contraintes garantissant l’injectivité de la déformation. De plus, la déformation du domaine paramétrique au lieu de l’objet lui-même permet l’utilisation de domaines plus généraux. Troisièmement, nous présentons une approche non linéaire basée sur les angles dièdres. Cette méthode définit la déformation du solide par les angles dièdres au lieu des positions des sommets du maillage. Ce changement de variables permet une expression naturelle des bornes de distorsion de la déformation. Nous présentons quelques applications de cette nouvelle approche dont la paramétrisation, l'interpolation, l'optimisation et la compression de maillages tétraédriques.
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Mann–Kendall non-parametric test was employed for observational trend detection of monthly, seasonal and annual precipitation of five meteorological subdivisions of Central Northeast India (CNE India) for different 30-year normal periods (NP) viz. 1889–1918 (NP1), 1919–1948 (NP2), 1949–1978 (NP3) and 1979–2008 (NP4). The trends of maximum and minimum temperatures were also investigated. The slopes of the trend lines were determined using the method of least square linear fitting. An application of Morelet wavelet analysis was done with monthly rainfall during June– September, total rainfall during monsoon season and annual rainfall to know the periodicity and to test the significance of periodicity using the power spectrum method. The inferences figure out from the analyses will be helpful to the policy managers, planners and agricultural scientists to work out irrigation and water management options under various possible climatic eventualities for the region. The long-term (1889–2008) mean annual rainfall of CNE India is 1,195.1 mm with a standard deviation of 134.1 mm and coefficient of variation of 11%. There is a significant decreasing trend of 4.6 mm/year for Jharkhand and 3.2 mm/day for CNE India. Since rice crop is the important kharif crop (May– October) in this region, the decreasing trend of rainfall during themonth of July may delay/affect the transplanting/vegetative phase of the crop, and assured irrigation is very much needed to tackle the drought situation. During themonth of December, all the meteorological subdivisions except Jharkhand show a significant decreasing trend of rainfall during recent normal period NP4. The decrease of rainfall during December may hamper sowing of wheat, which is the important rabi crop (November–March) in most parts of this region. Maximum temperature shows significant rising trend of 0.008°C/year (at 0.01 level) during monsoon season and 0.014°C/year (at 0.01 level) during post-monsoon season during the period 1914– 2003. The annual maximum temperature also shows significant increasing trend of 0.008°C/year (at 0.01 level) during the same period. Minimum temperature shows significant rising trend of 0.012°C/year (at 0.01 level) during postmonsoon season and significant falling trend of 0.002°C/year (at 0.05 level) during monsoon season. A significant 4– 8 years peak periodicity band has been noticed during September over Western UP, and 30–34 years periodicity has been observed during July over Bihar subdivision. However, as far as CNE India is concerned, no significant periodicity has been noticed in any of the time series.
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The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.
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Speckle Pattern Shearing Interferometrie (Shearografie) ist eine speckle-interferometrische Messmethode und zeichnet sich durch die ganzflächige, berührungslose Arbeitsweise, hohe räumliche Auflösung und hohe Messempfindlichkeit aus. Diese Dissertation beinhaltet die neue bzw. weitere Entwicklung der Shearografie zur qualitativen Schwingungsbeobachtung und zur quantitativen Schwingungsmessung. Für die qualitative Schwingungsbeobachtung in Echtzeit werden die Optimierung des Zeitmittelungsverfahrens und die neue entwickelte Online-Charakterisierung von Streifenmustern mit statistischen Verfahren vorgestellt. Auf dieser Basis können sowohl eine genaue Fehlstellen-Detektion bei der zerstörungsfreien Materialprüfung als auch eine präzise Resonanzuntersuchung zeitsparend und vollautomatisch durchgeführt werden. Für die quantitative Schwingungsmessung wird eine sog. dynamische Phasenschiebe-Technik neu entwickelt, welche durch die Einführung eines synchron zum Objekt schwingenden Referenzspiegels realisiert wird. Mit dieser Technik ermöglicht das Zeitmittelungsverfahren die Amplituden und Phasen einer Objektschwingung quantitativ zu ermitteln. Auch eine Weiterentwicklung des stroboskopischen Verfahrens in Kombination mit zeitlicher Phasenverschiebung wird in der Arbeit präsentiert, womit der gesamte Prozess der Schwingungsmessung und -rekonstruktion beschleunigt und automatisch durchgeführt wird. Zur Bestimmung des Verschiebungsfeldes aus den gemessenen Amplituden und Phasen des Verformungsgradienten stellt diese Arbeit auch eine Weiterentwicklung des Summationsverfahrens vor. Das Verfahren zeichnet sich dadurch aus, dass die Genauigkeit des ermittelten Verschiebungsfelds unabhängig von der Sheargröße ist und gleichzeitig das praktische Problem - Unstetigkeit - gelöst wird. Eine quantitative Messung erfordert eine genaue Kalibrierung der gesamten Messkette. Ein auf dem Least-Square-Verfahren basierendes Kalibrierverfahren wird in der Arbeit zur Kalibrierung der statischen und dynamischen Phasenverschiebung vorgestellt. Auch die Ermittelung der Sheargröße mit Hilfe der 1D- bzw. 2D-Kreuz-Korrelation wird präsentiert. Zum Schluss wurde die gesamte Entwicklung durch eine Vergleichsmessung mit einem handelsüblichen Scanning-Laser-Doppler-Vibrometer experimentell verifiziert.
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En esta Tesis se presenta el modelo de Kou, Difusión con saltos doble exponenciales, para la valoración de opciones Call de tipo europeo sobre los precios del petróleo como activo subyacente. Se mostrarán los cálculos numéricos para la formulación de expresiones analíticas que se resolverán mediante la implementación de algoritmos numéricos eficientes que conllevaran a los precios teóricos de las opciones evaluadas. Posteriormente se discutirán las ventajas de usar métodos como la transformada de Fourier por la sencillez relativa de su programación frente a los desarrollos de otras técnicas numéricas. Este método es usado en conjunto con el ejercicio de calibración no paramétrica de regularización, que mediante la minimización de los errores al cuadrado sujeto a una penalización fundamentada en el concepto de entropía relativa, resultaran en la obtención de precios para las opciones Call sobre el petróleo considerando una mejor capacidad del modelo de asignar precios justos frente a los transados en el mercado.
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We look at at the empirical validity of Schelling’s models for racial residential segregation applied to the case of Chicago. Most of the empirical literature has focused exclusively the single neighborhood model, also known as the tipping point model and neglected a multineighborhood approach or a unified approach. The multi-neighborhood approach introduced spatial interaction across the neighborhoods, in particular we look at spatial interaction across neighborhoods sharing a border. An initial exploration of the data indicates that spatial contiguity might be relevant to properly analyse the so call tipping phenomena of predominately non-Hispanic white neighborhoods to predominantly minority neighborhoods within a decade. We introduce an econometric model that combines an approach to estimate tipping point using threshold effects and a spatial autoregressive model. The estimation results from the model disputes the existence of a tipping point, that is a discontinuous change in the rate of growth of the non-Hispanic white population due to a small increase in the minority share of the neighborhood. In addition we find that racial distance between the neighborhood of interest and it surrounding neighborhoods has an important effect on the dynamics of racial segregation in Chicago.
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The anisotropic and isotropic components of the ν2, ν5 rotation-vibrational Raman bands of 13CH3F were obtained separately. The two upper states are coupled by a strong second-order Coriolis resonance. The anisotropic spectrum was analyzed by means of a program system due to R. Escribano. A contour simulation and a least-squares fit of 233 assigned transitions yielded values for ν5, ΔA5, ΔA2, and Aζ5a, 5b(z). The 13C shifts of ν2 and ν5 were obtained from the isotropic spectrum.
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This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.
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This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.