961 resultados para Orthogonal polynomial


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In this work, we present a generic formula for the polynomial solution families of the well-known differential equation of hypergeometric type s(x)y"n(x) + t(x)y'n(x) - lnyn(x) = 0 and show that all the three classical orthogonal polynomial families as well as three finite orthogonal polynomial families, extracted from this equation, can be identified as special cases of this derived polynomial sequence. Some general properties of this sequence are also given.

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Polynomial chaos expansion (PCE) with Latin hypercube sampling (LHS) is employed for calculating the vibrational frequencies of an inviscid incompressible fluid partially filled in a rectangular tank with and without a baffle. Vibration frequencies of the coupled system are described through their projections on the PCE which uses orthogonal basis functions. PCE coefficients are evaluated using LHS. Convergence on the coefficient of variation is used to find the orthogonal polynomial basis function order which is employed in PCE. It is observed that the dispersion in the eigenvalues is more in the case of a rectangular tank with a baffle. The accuracy of the PCE method is verified with standard MCS results and is found to be more efficient.

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This article surveys the classical orthogonal polynomial systems of the Hahn class, which are solutions of second-order differential, difference or q-difference equations. Orthogonal families satisfy three-term recurrence equations. Example applications of an algorithm to determine whether a three-term recurrence equation has solutions in the Hahn class - implemented in the computer algebra system Maple - are given. Modifications of these families, in particular associated orthogonal systems, satisfy fourth-order operator equations. A factorization of these equations leads to a solution basis.

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In this work, we have mainly achieved the following: 1. we provide a review of the main methods used for the computation of the connection and linearization coefficients between orthogonal polynomials of a continuous variable, moreover using a new approach, the duplication problem of these polynomial families is solved; 2. we review the main methods used for the computation of the connection and linearization coefficients of orthogonal polynomials of a discrete variable, we solve the duplication and linearization problem of all orthogonal polynomials of a discrete variable; 3. we propose a method to generate the connection, linearization and duplication coefficients for q-orthogonal polynomials; 4. we propose a unified method to obtain these coefficients in a generic way for orthogonal polynomials on quadratic and q-quadratic lattices. Our algorithmic approach to compute linearization, connection and duplication coefficients is based on the one used by Koepf and Schmersau and on the NaViMa algorithm. Our main technique is to use explicit formulas for structural identities of classical orthogonal polynomial systems. We find our results by an application of computer algebra. The major algorithmic tools for our development are Zeilberger’s algorithm, q-Zeilberger’s algorithm, the Petkovšek-van-Hoeij algorithm, the q-Petkovšek-van-Hoeij algorithm, and Algorithm 2.2, p. 20 of Koepf's book "Hypergeometric Summation" and it q-analogue.

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We discuss an old theorem of Obrechkoff and some of its applications. Some curious historical facts around this theorem are presented. We make an attempt to look at some known results on connection coefficients, zeros and Wronskians of orthogonal polynomials from the perspective of Obrechkoff's theorem. Necessary conditions for the positivity of the connection coefficients of two families of orthogonal polynomials are provided. Inequalities between the kth zero of an orthogonal polynomial p(n)(x) and the largest (smallest) zero of another orthogonal polynomial q(n)(x) are given in terms of the signs of the connection coefficients of the families {p(n)(x)} and {q(n)(x)}, An inequality between the largest zeros of the Jacobi polynomials P-n((a,b)) (x) and P-n((alpha,beta)) (x) is also established. (C) 2001 Elsevier B.V. B.V. All rights reserved.

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It is well known and easy to see that the zeros of both the associated polynomial and the derivative of an orthogonal polynomial p(n)(x) interlace with the zeros of p(n)(x) itself. The natural question of how these zeros interlace is under discussion. We give a sufficient condition for the mutual location of kth, 1 less than or equal to k less than or equal to n - 1, zeros of the associated polynomial and the derivative of an orthogonal polynomial in terms of inequalities for the corresponding Cotes numbers. Applications to the zeros of the associated polynomials and the derivatives of the classical orthogonal polynomials are provided. Various inequalities for zeros of higher order associated polynomials and higher order derivatives of orthogonal polynomials are proved. The results involve both classical and discrete orthogonal polynomials, where, in the discrete case, the differential operator is substituted by the difference operator. (C) 2001 IMACS. Published by Elsevier B.V. B.V. All rights reserved.

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In this paper the recurrence relations of symmetric orthogonal polynomials whose measures are related to each other in a certain way are considered. Many of the relations satisfied by the coefficients of the recurrence relations are exposed. The results are applied to obtain, for example, information regarding certain Sobolev orthogonal polynomials and regarding the measures of certain orthogonal polynomial sequences with twin periodic recurrence coefficients. (C) 2001 IMACS. Published by Elsevier B.V. B.V. All rights reserved.

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In this paper we analyze the location of the zeros of polynomials orthogonal with respect to the inner product where α >-1, N ≥ 0, and j ∈ N. In particular, we focus our attention on their interlacing properties with respect to the zeros of Laguerre polynomials as well as on the monotonicity of each individual zero in terms of the mass N. Finally, we give necessary and sufficient conditions in terms of N in order for the least zero of any Laguerre-Sobolev-type orthogonal polynomial to be negative. © 2011 American Mathematical Society.

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A discriminação de fases que são praticamente indistinguíveis ao microscópio ótico de luz refletida ou ao microscópio eletrônico de varredura (MEV) é um dos problemas clássicos da microscopia de minérios. Com o objetivo de resolver este problema vem sendo recentemente empregada a técnica de microscopia colocalizada, que consiste na junção de duas modalidades de microscopia, microscopia ótica e microscopia eletrônica de varredura. O objetivo da técnica é fornecer uma imagem de microscopia multimodal, tornando possível a identificação, em amostras de minerais, de fases que não seriam distinguíveis com o uso de uma única modalidade, superando assim as limitações individuais dos dois sistemas. O método de registro até então disponível na literatura para a fusão das imagens de microscopia ótica e de microscopia eletrônica de varredura é um procedimento trabalhoso e extremamente dependente da interação do operador, uma vez que envolve a calibração do sistema com uma malha padrão a cada rotina de aquisição de imagens. Por esse motivo a técnica existente não é prática. Este trabalho propõe uma metodologia para automatizar o processo de registro de imagens de microscopia ótica e de microscopia eletrônica de varredura de maneira a aperfeiçoar e simplificar o uso da técnica de microscopia colocalizada. O método proposto pode ser subdividido em dois procedimentos: obtenção da transformação e registro das imagens com uso desta transformação. A obtenção da transformação envolve, primeiramente, o pré-processamento dos pares de forma a executar um registro grosseiro entre as imagens de cada par. Em seguida, são obtidos pontos homólogos, nas imagens óticas e de MEV. Para tal, foram utilizados dois métodos, o primeiro desenvolvido com base no algoritmo SIFT e o segundo definido a partir da varredura pelo máximo valor do coeficiente de correlação. Na etapa seguinte é calculada a transformação. Foram empregadas duas abordagens distintas: a média ponderada local (LWM) e os mínimos quadrados ponderados com polinômios ortogonais (MQPPO). O LWM recebe como entradas os chamados pseudo-homólogos, pontos que são forçadamente distribuídos de forma regular na imagem de referência, e que revelam, na imagem a ser registrada, os deslocamentos locais relativos entre as imagens. Tais pseudo-homólogos podem ser obtidos tanto pelo SIFT como pelo método do coeficiente de correlação. Por outro lado, o MQPPO recebe um conjunto de pontos com a distribuição natural. A análise dos registro de imagens obtidos empregou como métrica o valor da correlação entre as imagens obtidas. Observou-se que com o uso das variantes propostas SIFT-LWM e SIFT-Correlação foram obtidos resultados ligeiramente superiores aos do método com a malha padrão e LWM. Assim, a proposta, além de reduzir drasticamente a intervenção do operador, ainda possibilitou resultados mais precisos. Por outro lado, o método baseado na transformação fornecida pelos mínimos quadrados ponderados com polinômios ortogonais mostrou resultados inferiores aos produzidos pelo método que faz uso da malha padrão.

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Sediment samples were collected from the lower channel of the Yangtze River and the Yellow River and the contents of rare earth elements (REEs) were measured. In addition, some historical REEs data were collected from published literatures. Based on the delta Eu-N-I REEs pound plot, a clear boundary was found between the sediments from the two rivers. The boundary can be described as an orthogonal polynomial equation by ordinary linear regression with sediments from the Yangtze River located above the curve and sediments from the Yellow River located below the curve. To validate this method, the REEs contents of sediments collected from the estuaries of the Yangtze River and the Yellow River were measured. In addition, the REEs data of sediment Core 255 from the Yangtze River and Core YA01 from the Yellow River were collected. Results show that the samples from the Yangtze River estuary and Core 255 almost are above the curve and most samples from the Yellow River estuary and Core YA01 are below the curve in the delta Eu-N-I REEs pound plot. The plot and the regression equation can be used to distinguish sediments from the Yangtze River and the Yellow River intuitively and quantitatively, and to trace the sediment provenance of the eastern seas of China. The difference between the sediments from two rivers in the delta Eu-N-I REEs pound plot is caused by different mineral compositions and regional climate patterns of the source areas. The relationship between delta Eu-N and I REEs pound is changed little during the transport from the source area to the river, and from river to the sea. Thus the original information on mineral compositions and climate of the source area was preserved.

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Seismic Numerical Modeling is one of bases of the Exploratory Seismology and Academic Seismology, also is a research field in great demand. Essence of seismic numerical modeling is to assume that structure and parameters of the underground media model are known, simulate the wave-field and calculate the numerical seismic record that should be observed. Seismic numerical modeling is not only a means to know the seismic wave-field in complex inhomogeneous media, but also a test to the application effect by all kinds of methods. There are many seismic numerical modeling methods, each method has its own merits and drawbacks. During the forward modeling, the computation precision and the efficiency are two pivotal questions to evaluate the validity and superiority of the method. The target of my dissertation is to find a new method to possibly improve the computation precision and efficiency, and apply the new forward method to modeling the wave-field in the complex inhomogeneous media. Convolutional Forsyte polynomial differentiator (CFPD) approach developed in this dissertation is robust and efficient, it shares some of the advantages of the high precision of generalized orthogonal polynomial and the high speed of the short operator finite-difference. By adjusting the operator length and optimizing the operator coefficient, the method can involve whole and local information of the wave-field. One of main tasks of the dissertation is to develop a creative, generalized and high precision method. The author introduce convolutional Forsyte polynomial differentiator to calculate the spatial derivative of seismic wave equation, and apply the time staggered grid finite-difference which can better meet the high precision of the convolutional differentiator to substitute the conventional finite-difference to calculate the time derivative of seismic wave equation, then creating a new forward method to modeling the wave-field in complex inhomogeneous media. Comparing with Fourier pseudo-spectral method, Chebyshev pseudo-spectral method, staggered- grid finite difference method and finite element method, convolutional Forsyte polynomial differentiator (CFPD) method has many advantages: 1. Comparing with Fourier pseudo-spectral method. Fourier pseudo-spectral method (FPS) is a local operator, its results have Gibbs effects when the media parameters change, then arose great errors. Therefore, Fourier pseudo-spectral method can not deal with special complex and random heterogeneous media. But convolutional Forsyte polynomial differentiator method can cover global and local information. So for complex inhomogeneous media, CFPD is more efficient. 2. Comparing with staggered-grid high-order finite-difference method, CFPD takes less dots than FD at single wave length, and the number does not increase with the widening of the studying area. 3. Comparing with Chebyshev pseudo-spectral method (CPS). The calculation region of Chebyshev pseudo-spectral method is fixed in , under the condition of unchangeable precision, the augmentation of calculation is unacceptable. Thus Chebyshev pseudo-spectral method is inapplicable to large area. CFPD method is more applicable to large area. 4. Comparing with finite element method (FE), CFPD can use lager grids. The other task of this dissertation is to study 2.5 dimension (2.5D) seismic wave-field. The author reviews the development and present situation of 2.5D problem, expatiates the essentiality of studying the 2.5D problem, apply CFPD method to simulate the seismic wave-field in 2.5D inhomogeneous media. The results indicate that 2.5D numerical modeling is efficient to simulate one of the sections of 3D media, 2.5D calculation is much less time-consuming than 3D calculation, and the wave dispersion of 2.5D modeling is obviously less than that of 3D modeling. Question on applying time staggered-grid convolutional differentiator based on CFPD to modeling 2.5D complex inhomogeneous media was not studied by any geophysicists before, it is a fire-new creation absolutely. The theory and practices prove that the new method can efficiently model the seismic wave-field in complex media. Proposing and developing this new method can provide more choices to study the seismic wave-field modeling, seismic wave migration, seismic inversion, and seismic wave imaging.

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The theory researches of prediction about stratigraphic filtering in complex condition are carried out, and three key techniques are put forward in this dissertation. Theoretical aspects: The prediction equations for both slant incidence in horizontally layered medium and that in laterally variant velocity medium are expressed appropriately. Solving the equations, the linear prediction operator of overlaid layers, then corresponding reflection/transmission operators, can be obtained. The properties of linear prediction operator are elucidated followed by putting forward the event model for generalized Goupillaud layers. Key technique 1: Spectral factorization is introduced to solve the prediction equations in complex condition and numerical results are illustrated. Key technique 2: So-called large-step wavefield extrapolation of one-way wave under laterally variant velocity circumstance is studied. Based on Lie algebraic integral and structure preserving algorithm, large-step wavefield depth extrapolation scheme is set forth. In this method, the complex phase of wavefield extrapolation operator’s symbol is expressed as a linear combination of wavenumbers with the coefficients of this linear combination in the form of the integral of interval velocity and its derivatives over depth. The exponential transform of the complex phase is implemented through phase shifting, BCH splitting and orthogonal polynomial expansion. The results of numerical test show that large-step scheme takes on a great number of advantages as low accumulating error, cheapness, well adaptability to laterally variant velocity, small dispersive, etc. Key technique 3: Utilizing large-step wavefield extrapolation scheme and based on the idea of local harmonic decomposition, the technique generating angle gathers for 2D case is generalized to 3D case so as to solve the problems generating and storing 3D prestack angle gathers. Shot domain parallel scheme is adopted by which main duty for servant-nodes is to compute trigonometric expansion coefficients, while that for host-node is to reclaim them with which object-oriented angle gathers yield. In theoretical research, many efforts have been made in probing into the traits of uncertainties within macro-dynamic procedures.

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In this paper, we propose a new numerical modeling method – Convolutional Forsyte Polynomial Differentiator (CFPD), aimed at simulating seismic wave propagation in complex media with high efficiency and accuracy individually owned by short-scheme finite differentiator and general convolutional polynomial method. By adjusting the operator length and optimizing the operator coefficient, both global and local informations can be easily incorporated into the wavefield which is important to invert the undersurface geological structure. The key issue in this paper is to introduce the convolutional differentiator based on Forsyte generalized orthogonal polynomial in mathematics into the spatial differentiation of the first velocity-stress equation. To match the high accuracy of the spatial differentiator, this method in the time coordinate adopts staggered grid finite difference instead of conventional finite difference to model seismic wave propagation in heterogeneous media. To attenuate the reflection artifacts caused by artificial boundary, Perfectly Matched Layer (PML) absorbing boundary is also being considered in the method to deal with boundary problem due to its advantage of automatically handling large-angle emission. The PML formula for acoustic equation and first-order velocity-stress equation are also derived in this paper. There is little difference to implement the PML boundary condition in all kind of wave equations, but in Biot media, special attenuation factors should be taken. Numerical results demonstrate that the PML boundary condition is better than Cerjan absorbing boundary condition which makes it more suitable to hand the artificial boundary reflection. Based on the theories of anisotropy, Biot two-phase media and viscous-elasticity, this paper constructs the constitutive relationship for viscous-elastic and two-phase media, and further derives the first-order velocity-stress equation for 3D viscous-elastic and two-phase media. Numerical modeling using CFPD method is carried out in the above-mentioned media. The results modeled in the viscous-elastic media and the anisotropic pore elastic media can better explain wave phenomena of the true earth media, and can also prove that CFPD is a useful numerical tool to study the wave propagation in complex media.

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The main aim of this paper is the development of suitable bases (replacing the power basis x^n (n\in\IN_\le 0) which enable the direct series representation of orthogonal polynomial systems on non-uniform lattices (quadratic lattices of a discrete or a q-discrete variable). We present two bases of this type, the first of which allows to write solutions of arbitrary divided-difference equations in terms of series representations extending results given in [16] for the q-case. Furthermore it enables the representation of the Stieltjes function which can be used to prove the equivalence between the Pearson equation for a given linear functional and the Riccati equation for the formal Stieltjes function. If the Askey-Wilson polynomials are written in terms of this basis, however, the coefficients turn out to be not q-hypergeometric. Therefore, we present a second basis, which shares several relevant properties with the first one. This basis enables to generate the defining representation of the Askey-Wilson polynomials directly from their divided-difference equation. For this purpose the divided-difference equation must be rewritten in terms of suitable divided-difference operators developed in [5], see also [6].

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Foram utilizados quatorze modelos de regressão aleatória, para ajustar 86.598 dados de produção de leite no dia do controle de 2.155 primeiras lactações de vacas Caracu, truncadas aos 305 dias. Os modelos incluíram os efeitos fixos de grupo contemporâneo e a covariável idade da vaca ao parto. Uma regressão ortogonal de ordem cúbica foi usada para modelar a trajetória média da população. Os efeitos genéticos aditivos e de ambiente permanente foram modelados por meio de regressões aleatórias, usando polinômios ortogonais de Legendre, de ordens cúbicas. Diferentes estruturas de variâncias residuais foram testadas e consideradas por meio de classes contendo 1, 10, 15 e 43 variâncias residuais e de funções de variâncias (FV) usando polinômios ordinários e ortogonais, cujas ordens variaram de quadrática até sêxtupla. Os modelos foram comparados usando o teste da razão de verossimilhança, o Critério de Informação de Akaike e o Critério de Informação Bayesiano de Schwar. Os testes indicaram que, quanto maior a ordem da função de variâncias, melhor o ajuste. Dos polinômios ordinários, a função de sexta ordem foi superior. Os modelos com classes de variâncias residuais foram aparentemente superiores àqueles com funções de variância. O modelo com homogeneidade de variâncias foi inadequado. O modelo com 15 classes heterogêneas foi o que melhor ajustou às variâncias residuais, entretanto, os parâmetros genéticos estimados foram muito próximos para os modelos com 10, 15 ou 43 classes de variâncias ou com FV de sexta ordem.