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| Author(s): |
Ana Carolina Camargo
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica |
| Defense date: | 2006-03-29 |
| Examining board members: |
Lucio Tunes dos Santos;
Alvaro Rodolfo De Pierro;
Rodrigo de Souza Portugal
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| Advisor: | Lucio Tunes dos Santos |
| Abstract | |
Its common to be needed to reconstruct functions which samples falls on a nonequally spaced grid. This is due to the fact that some of the most used algorithms require samples in a regular (uniform) Cartesian grid. Therefore, it is necessary to make an uniform resampling, i.e., to interpolate the nonuniform samples in a set of equally spaced points. In this work, it is first shown that the resampling problem can be formulated as a problem of solving a system of linear equations. A solution for this system can be found using the pseudoinverse matrix, a process that is impractical for a large number of variables. From particular characteristics of the problem, it is possible to develop a better algorithm, which only uses a limited number of samples to calculate each uniform sample, transforming the original problem into a sequence of linear systems with less variables. The final result can be viewed as both optimal and computationally efficient. Applications are presented to demonstrate the efficiency of the method (AU) | |