983 resultados para Legendre Polynomial Dipole Moment Generating Function


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Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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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.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This work presents a theoretical and numerical analysis of Frequency Selective Surfaces (FSS) with elements as rectangular patch, thin dipole and crossed dipole mounted on uniaxial anisotropic dielectric substrate layers for orientations of the optical axis along x, y and z directions. The analysis of these structures is accomplished by combination of the Hertz vector potentials method and the Galerkin's technique, in the Fourier transform-domain, using entire¬domain basis functions. This study consists in the use of one more technique for analysis of FSS on anisotropic dielectric substrate. And presents as the main contribution the introduction of one more project parameter to determinate the transmission and reflection characteristics of periodic structures, from the use of anisotropic dielectric with orientations of the crystal optical axis along x, y and z directions. To validate this analysis, the numerical results of this work are compared to those obtained by other authors, for FSS structures on anisotropic and isotropic dielectric substrates. Also are compared experimental results and the numerical correspondent ones for the FSS isotropic case. The technique proposed in this work is accurate and efficient. ln a second moment, curves are presented for the transmission and reflection characteristics of the FSS structures using conducting patch elements mounted on uniaxial anisotropic dielectric substrate layers with optical axis oriented along x, y and z directions. From analysis of these curves, the performance of the considered FSS structures as function of the optical axis orientation is described

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Information retrieval is of paramount importance in all areas of knowledge. Regarding the temperatures of Natal, they were simulated and analyzed. Thus, it was possible to recover, with some accuracy, the temperatures of days they were not collected. For this we constructed a software that displays the temperature value at each moment in the city. The program was developed in Delphi using interpolated polynomial function of third degree. The equations were obtained in Excel and data were collected at the Instituto Nacional de Pesquisas Espaciais (INPE). These functions were changed from a correction factor in order to provide values to temperatures between those who were not collected. Armed with this program you can build tables and charts to analyze the temperatures for certain periods of time. The same analysis was done by developing mathematical functions that describes the temperatures. With the data provided by this software is possible to say which are the hours of highest and lowest temperatures in the city, as the months have indexes with the highest and lowest temperatures.

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The effect of finite size on the magnetic properties of ferromagnetic particles systems is a recurrent subject. One of the aspects wide investigated is the superparamagnetic limit where the temperature destroys the magnetic order of ferromagnetic small particles. Above the block temperature the thermal value of the magnetic moment of the particle vanishes, due to thermal fluctuations. The value of the blocking temperature diminishes when the size of the particle is reduced, reflecting the reduction of the anisotropy energy barrier between the uniform states along the uniaxial axis. The increasing demand for high density magnetic media has recently attracted great research interest in periodic arrangements of nanometric ferromagnetics particles, approach in the superparamagnetic limit. An interesting conjecture is the possibility of stabilization of the magnetic order of small ferromagnetic particles (F) by interface coupling with antiferromagnetic (AF) substrate. These F/AF systems may also help to elucidate some details of the effect of exchange bias, because the effect of interface roughness and the paper of domain walls, either in the substrate or the particle, are significantly reduced. We investigate the magnetic phases of small ferromagnetic particles on a antiferromagnetic substrate. We use a self-consistent local field method, incorporating the interface field and the dipole interaction between the spins of the ferromagnetic particle. Our results indicate that increasing the area of the interface favors the formation of the uniform state. Howere above a critical height value appears a state non-uniform is formed where the spins of in the particle s free surface are rotated with respect to the interface spins direction. We discuss the impact of the competition between the dipolar and interface field on the magnetic charge, that controls the field of flux leakage of the particle, and on the format of the hysteresis curves. Our results indicate that the liquid magnetic charge is not a monotonically increasing function of the height of the particle. The exchange bias may display anomalous features, induced for the dipolar field of the spins near the F/AF interface

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Wavelet functions have been used as the activation function in feedforward neural networks. An abundance of R&D has been produced on wavelet neural network area. Some successful algorithms and applications in wavelet neural network have been developed and reported in the literature. However, most of the aforementioned reports impose many restrictions in the classical backpropagation algorithm, such as low dimensionality, tensor product of wavelets, parameters initialization, and, in general, the output is one dimensional, etc. In order to remove some of these restrictions, a family of polynomial wavelets generated from powers of sigmoid functions is presented. We described how a multidimensional wavelet neural networks based on these functions can be constructed, trained and applied in pattern recognition tasks. As an example of application for the method proposed, it is studied the exclusive-or (XOR) problem.

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The study of robust design methodologies and techniques has become a new topical area in design optimizations in nearly all engineering and applied science disciplines in the last 10 years due to inevitable and unavoidable imprecision or uncertainty which is existed in real word design problems. To develop a fast optimizer for robust designs, a methodology based on polynomial chaos and tabu search algorithm is proposed. In the methodology, the polynomial chaos is employed as a stochastic response surface model of the objective function to efficiently evaluate the robust performance parameter while a mechanism to assign expected fitness only to promising solutions is introduced in tabu search algorithm to minimize the requirement for determining robust metrics of intermediate solutions. The proposed methodology is applied to the robust design of a practical inverse problem with satisfactory results.

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In this paper we get some lower bounds for the number of critical periods of families of centers which are perturbations of the linear one. We give a method which lets us prove that there are planar polynomial centers of degree l with at least 2[(l - 2)/2] critical periods as well as study concrete families of potential, reversible and Lienard centers. This last case is studied in more detail and we prove that the number of critical periods obtained with our approach does not. increases with the order of the perturbation. (C) 2007 Elsevier Ltd. All rights reserved.

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The main purpose of this paper is to investigate theoretically and experimentally the use of family of Polynomial Powers of the Sigmoid (PPS) Function Networks applied in speech signal representation and function approximation. This paper carries out practical investigations in terms of approximation fitness (LSE), time consuming (CPU Time), computational complexity (FLOP) and representation power (Number of Activation Function) for different PPS activation functions. We expected that different activation functions can provide performance variations and further investigations will guide us towards a class of mappings associating the best activation function to solve a class of problems under certain criteria.

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For any positive integer n, the sine polynomials that are nonnegative in [0, π] and which have the maximal derivative at the origin are determined in an explicit form. Associated cosine polynomials Kn (θ) are constructed in such a way that {Kn(θ)} is a summability kernel. Thus, for each Pi 1 ≤ P ≤ ∞ and for any 27π-periodic function f ∈ Lp [-π, π], the sequence of convolutions Kn * f is proved to converge to f in Lp[-ππ]. The pointwise and almost everywhere convergences are also consequences of our construction.

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A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. The results indicate that the network presents good approximation capability even with severe quantization. The parameter quantization decreases the memory size and circuit complexity required to store the network parameters leading to compact mixed-signal circuits proper for low-power applications. ©2008 IEEE.