Este trabalho consiste na análise do comportamento do método WAMG (Wavelet-Based Algebraic Multigrid), método numérico de resolução de sistemas de equações lineares desenvolvido no LMAG-Laboratório de Eletromagnetismo Aplicado, com relação a diversos suavizadores. O fato dos vetores que compõem os operadores matriciais Pronlongamento e Restrição do método WAMG serem ortonormais viabiliza uma série de análises teóricas e de dados experimentais, permitindo visualizar características não permitidas nos outros métodos Multigrid (MG), englobando o Multigrid Geométrico (GMG) e o Multigrid Algébrico (AMG). O método WAMG V-Cycle com Filtro Haar é testado em uma variedade de sistemas de equações lineares variando o suavizador, o coeficiente de relaxação nos suavizadores Damped Jacobi e Sobre Relaxação Sucessiva (SOR), e a configuração de pré e pós-suavização. Entre os suavizadores testados, estão os métodos iterativos estacionários Damped Jacobi, SOR, Esparsa Aproximada a Inversa tipo Diagonal (SPAI-0) e métodos propostos com a característica de suavização para-otimizada. A título de comparação, métodos iterativos não estacionários são testados também como suavizadores como Gradientes Conjugados, Gradientes Bi-Conjugados e ICCG. Os resultados dos testes são apresentados e comentados. / This work is comprised of WAMG (Wavelet-Based Algebraic Multigrid) method behavioral analysis based on variety of smoothers, numerical method based on linear equation systems resolution developed at LMAG (Applied Electromagnetism Laboratory). Based on the fact that the vectors represented by WAMG Prolongation and Restriction matrix operators are orthonormals allows the use of a variety of theoretical and practical analysis, and therefore gain visibility of characteristics not feasible through others Multigrid (MG) methods, such as Geometric Multigrid (GMG) and Algebraic Multigrid (AMG). WAMG V-Cycle method with Haar Filter is tested under a variety of linear equation systems, by varying smoothers, relaxation coefficient at Damped Jacobi and Successive Over Relaxation (SOR) smoothers, and pre and post smoothers configurations. The tested smoothers are stationary iterative methods such as Damped Jacobi, SOR, Diagonal type-Sparse Approximate Inverse (SPAI-0) and suggested ones with optimized smoothing characteristic. For comparison purposes, the Conjugate Gradients, Bi-Conjugate Gradient and ICCG non-stationary iterative methods are also tested as smoothers. The testing results are formally presented and commented.

Este trabalho consiste na análise do comportamento do método WAMG (Wavelet-Based Algebraic Multigrid), método numérico de resolução de sistemas de equações lineares desenvolvido no LMAG-Laboratório de Eletromagnetismo Aplicado, com relação a diversos suavizadores. O fato dos vetores que compõem os operadores matriciais Pronlongamento e Restrição do método WAMG serem ortonormais viabiliza uma série de análises teóricas e de dados experimentais, permitindo visualizar características não permitidas nos outros métodos Multigrid (MG), englobando o Multigrid Geométrico (GMG) e o Multigrid Algébrico (AMG). O método WAMG V-Cycle com Filtro Haar é testado em uma variedade de sistemas de equações lineares variando o suavizador, o coeficiente de relaxação nos suavizadores Damped Jacobi e Sobre Relaxação Sucessiva (SOR), e a configuração de pré e pós-suavização. Entre os suavizadores testados, estão os métodos iterativos estacionários Damped Jacobi, SOR, Esparsa Aproximada a Inversa tipo Diagonal (SPAI-0) e métodos propostos com a característica de suavização para-otimizada. A título de comparação, métodos iterativos não estacionários são testados também como suavizadores como Gradientes Conjugados, Gradientes Bi-Conjugados e ICCG. Os resultados dos testes são apresentados e comentados. / This work is comprised of WAMG (Wavelet-Based Algebraic Multigrid) method behavioral analysis based on variety of smoothers, numerical method based on linear equation systems resolution developed at LMAG (Applied Electromagnetism Laboratory). Based on the fact that the vectors represented by WAMG Prolongation and Restriction matrix operators are orthonormals allows the use of a variety of theoretical and practical analysis, and therefore gain visibility of characteristics not feasible through others Multigrid (MG) methods, such as Geometric Multigrid (GMG) and Algebraic Multigrid (AMG). WAMG V-Cycle method with Haar Filter is tested under a variety of linear equation systems, by varying smoothers, relaxation coefficient at Damped Jacobi and Successive Over Relaxation (SOR) smoothers, and pre and post smoothers configurations. The tested smoothers are stationary iterative methods such as Damped Jacobi, SOR, Diagonal type-Sparse Approximate Inverse (SPAI-0) and suggested ones with optimized smoothing characteristic. For comparison purposes, the Conjugate Gradients, Bi-Conjugate Gradient and ICCG non-stationary iterative methods are also tested as smoothers. The testing results are formally presented and commented.

In this thesis, we propose a novel hyper-rectangle cover theory which provides a new approach to analyzing mathematical problems with nonnegativity constraints on variables. In this theory, two fundamental concepts, cover order and cover length, are introduced and studied in details. In the same manner as determining the rank of a matrix, we construct a specific e ́chelon form of the matrix to obtain the cover order of a given matrix efficiently and effectively. We discuss various structures of the e ́chelon form for some special cases in detail. Based on the structure and properties of the constructed e ́chelon form, the concepts of non-negatively linear independence and non-negatively linear dependence are developed. Using the properties of the cover order, we obtain the necessary and sufficient conditions for the existence and uniqueness of the solutions for linear equations system with nonnegativity constraints on variables for both homogeneous and non-homogeneous cases. In addition, we apply the cover theory to analyze some typical problems in linear algebra and optimization with nonnegativity constraints on variables, including linear programming problems and non-negative least squares (NNLS) problems. For linear programming problem, we study the three possible behaviors of the solutions for it through hyper-rectangle cover theory, and show that a series of feasible solutions for the problem with the zero-cover e ́chelon form structure. On the other hand, we develop a method to obtain the cover length of the covered variable. In the process, we discover the relationship between the cover length determination problem and the NNLS problem. This enables us to obtain an analytical optimal value for the NNLS problem. / Thesis / Doctor of Philosophy (PhD)