948 resultados para Equações diferenciais elipticas


Relevância:

10.00% 10.00%

Publicador:

Resumo:

This work consists on the theoretical and numerical analysis of some properties of circular microstrip patch antennas on isotropic and uniaxial anisotropic substrates. For this purpose, a full wave analysis is performed, using Hertz Vector Potentials method in the Hankel Transform domain. In the numerical analysis, the moment method is also used in order to determine some characteristics of the antenna, such as: resonant frequency and radiation pattern. The definition of Hertz potentials in the Hankel domain is used in association with Maxwell´s equations and the boundary conditions of the structures to obtain the Green´s functions, relating the components of the current density on the patch and the tangential electric field components. Then, the Galerkin method is used to generate a matrix equation whose nontrivial solution is the complex resonant frequency of the structure. In the analysis, a microstrip antenna with only one isotropic dielectric layer is initially considered. For this structure, the effect of using superconductor patches is also analyzed. An analysis of a circular microstrip antenna on an uniaxial anisotropic dielectric layer is performed, using the Hertz vector potentials oriented along the optical axis of the material, that is perpendicular to the microstrip ground plane. Afterwards, the circular microstrip antenna using two uniaxial anisotropic dielectric layers is investigated, considering the particular case in which the inferior layer is filled by air. In this study, numerical results for resonant frequency and radiation pattern for circular microstrip antennas on isotropic and uniaxial anisotropic substrates are presented and compared with measured and calculated results found in the literature

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Recently the planar antennas have been studied due to their characteristics as well as the advantages that they offers when compared with another types of antennas. In the mobile communications area, the need for this kind of antennas have became each time bigger due to the intense increase of the mobile communications that needs of antennas which operate in multifrequency and wide bandwidth. The microstrip antennas presents narrow bandwidth due the loss in the dielectric generated by radiation. Another limitation is the radiation pattern degradation due the generation of surface waves in the substrate. In this work some used techniques to minimize the disadvantages (previously mentioned) of the use of microstrip antennas are presented, those are: substrates with PBG material - Photonic Bandgap, multilayer antennas and with stacked patches. The developed analysis in this work used the TTL - Transverse Transmission Line method in the domain of Fourier transform, that uses a component of propagation in the y direction (transverse to the direction real of propagation z), treating the general equations of electric and magnetic field as functions of y and y . This work has as objective the application of the TTL method to microstrip structures with single and multilayers of rectangular and triangular patches, to obtaining the resonance frequency and radiation pattern of each structure. This method is applied for the treatment of the fields in stacked structures. The Homogenization theory will be applied to obtaining the effective permittivity for s and p polarizations of the substrate composed of PBG material. Numerical results for the triangular and rectangular antennas with single layer, multilayers resonators with triangular and rectangular patches are presented (in photonic and isotropic substrates). Conclusions and suggestions for continuity of this work are presented

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers