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Signal and image processing is important in a wide range of areas, including medical and astronomical imaging, and speech and acoustic signal processing. There is often a need for the reconstruction of these objects to be very fast, as they have some cost (perhaps a monetary cost, although often it is a time cost) attached to them. This work considers the development of algorithms that allow these signals and images to be reconstructed quickly and without perceptual quality loss. The main problem considered here is that of reducing the amount of time needed for images to be reconstructed, by decreasing the amount of data necessary for a high quality image to be produced. In addressing this problem two basic ideas are considered. The first is a subset selection problem where the aim is to extract a subset of data, of a predetermined size, from a much larger data set. To do this we first need some metric with which to measure how `good' (or how close to `best') a data subset is. Then, using this metric, we seek an algorithm that selects an appropriate data subset from which an accurate image can be reconstructed. Current algorithms use a criterion based upon the trace of a matrix. In this work we derive a simpler criterion based upon the determinant of a matrix. We construct two new algorithms based upon this new criterion and provide numerical results to demonstrate their accuracy and efficiency. A row exchange strategy is also described, which takes a given subset and performs interchanges to improve the quality of the selected subset. The second idea is, given a reduced set of data, how can we quickly reconstruct an accurate signal or image? Compressed sensing provides a mathematical framework that explains that if a signal or image is known to be sparse relative to some basis, then it may be accurately reconstructed from a reduced set of data measurements. The reconstruction process can be posed as a convex optimization problem. We introduce an algorithm that aims to solve the corresponding problem and accurately reconstruct the desired signal or image. The algorithm is based upon the Barzilai-Borwein algorithm and tailored specifically to the compressed sensing framework. Numerical experiments show that the algorithm is competitive with currently used algorithms. Following the success of compressed sensing for sparse signal reconstruction, we consider whether it is possible to reconstruct other signals with certain structures from reduced data sets. Specifically, signals that are a combination of a piecewise constant part and a sparse component are considered. A reconstruction process for signals of this type is detailed and numerical results are presented.

The purpose of this dissertation is to provide a theoretical model to design RF coils using multiconductor transmission line (MTL) structures for MRI applications. In this research, an MTL structure is represented as a multiport network using its port admittance matrix. Resonant conditions and closed-form solutions for different port resonant modes are calculated by solving the eigenvalue problem of port admittance matrix using block matrix algebra. A mathematical proof to show that the solution of the characteristic equation of the port admittance matrix is equivalent to solving the source side input impedance is presented. The proof is derived by writing the transmission chain parameter matrix of an MTL structure, and mathematically manipulating the chain parameter matrix to produce a solution to the characteristic equation of the port admittance matrix. A port admittance matrix can be formulated to take one of the forms depending on the type of MTL structure: a circulant matrix, or a circulant block matrix (CB), or a block circulant circulant block matrix (BCCB). A circulant matrix can be diagonalized by a simple Fourier matrix, and a BCCB matrix can be diagonalized by using matrices formed from Kronecker products of Fourier matrices. For a CB matrix, instead of diagonalizing to compute the eigenvalues, a powerful technique called “reduced dimension method� can be used. In the reduced dimension method, the eigenvalues of a circulant block matrix are computed as a set of the eigenvalues of matrices of reduced dimension. The required reduced dimension matrices are created using a combination of the polynomial representor of a circulant matrix and a permutation matrix. A detailed mathematical formulation of the reduced dimension method is presented in this thesis. With the application of the reduced dimension method for a 2n+1 MTL structure, the computation of eigenvalues for a 4n X 4n port admittance matrix is simplified to the computation of eigenvalues of 2n matrices of size 2 X 2. In addition to reduced computations, the model also facilitates analytical formulations for coil resonant conditions. To demonstrate the effectiveness of the proposed methods (2n port model and reduced dimension method), a two-step approach was adopted. First, a standard published RF coil was analyzed using the proposed models. The obtained resonant conditions are then compared with the published values and are verified by full-wave numerical simulations. Second, two new dual tuned coils, a surface coil design using the 2n port model, and a volume coil design using the reduced dimensions method are proposed, constructed, and bench tested. Their validation was carried out by employing 3D EM simulations as well as undertaking MR imaging on clinical scanners. Imaging experiments were conducted on phantoms, and the investigations indicate that the RF coils achieve good performance characteristics and a high signal-to-noise ratio in the regions of interest.

Basic idea of fractal simplex algorithm is based in the theory of matrix counting and knowledge of matrix representation of simplex tabuleao from revised simplex method. My desire is to explain theoretical basics on which this algorithm works and provide solution in language Visual Basic for Applications in application MS Excel 2007. Main benefit I see in the fact, that algorithm can solved specific class of mathematical problems in a way of exactness counting whithout necessity of using decimal numbers.

No / In this research work the improvement of AOA estimation accuracy by applying a decoupling matrix derived using the receiving mode approach has been investigated using data measured in an anechoic chamber. The receiver was a 4-element uniform circular array with quarter wavelength inter-element spacing deployed on a square metal plate. The performance of the angle of arrival estimation error has been observed for two groups of direction finding algorithms, namely phase comparison-based (interferometry) and covariance-based algorithms. Mutual coupling compensation on AOA was found to improve accuracy by approximately 50%.

No / A comparison between two indoor localization algorithms using received signal strength is carried out. The first algorithm is the vector algorithm; the second is the matrix algorithm. The comparison considered the effects of the reference points, the access point, and the frequency on the accuracy of the localization process. The experiments were carried out using ray tracing software and MATLAB. This paper justifies the use of adopting the matrix algorithm.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-07-25T16:54:03Z No. of bitstreams: 1 MACIEL MEDEIROS DE OLIVEIRA - DISSERTAÇÃO PPGMAT 2010..pdf: 998582 bytes, checksum: 142de66a057d7d36764dfcef2f50590c (MD5) / Made available in DSpace on 2018-07-25T16:54:03Z (GMT). No. of bitstreams: 1 MACIEL MEDEIROS DE OLIVEIRA - DISSERTAÇÃO PPGMAT 2010..pdf: 998582 bytes, checksum: 142de66a057d7d36764dfcef2f50590c (MD5) Previous issue date: 2010-12 / Capes / Neste trabalho fazemos uma abordagem sobre as identidades polinomiais da álgebra das matrizes Mn(K), onde K é um corpo. Inicialmente, apresentamos as provas de Rosset e Swan para o Teorema de Amitsur-Levitzki. Em seguida, fazemos um estudo sobre as identidades de Mn(K) de grau2n+1 para n >2 (considerando charK=0) e fechamos essa abordagem com a apresentação da resposta de Chang para a questão sugeridaporFormaneksobreminimalidadedeuminteiropositivomtalqueopolinômio duplo de Capelli Dm é uma identidade para Mn(K). / In this work we approach polinomial identities of the algebra of matrix Mn(K), whereK isafield. Initially, we present the Rosset’s and Swan’s proofs for the Theorem of Amitsur-Levitzki. Afterward, we make a study on the identities of Mn(K) of2n+1 degree (considering charK =0). We end this approach with the presentation of the minimality of a integer positive number m such that the Capelli double polinomial Dm is an identity of Mn(K).

Made available in DSpace on 2016-06-02T20:28:28Z (GMT). No. of bitstreams: 1 5476.pdf: 893744 bytes, checksum: e444c4faa79c02073abeef63581d7ed5 (MD5) Previous issue date: 2013-08-27 / Financiadora de Estudos e Projetos / In this work we present some applications of graph theory in problems involving polynomial identities for the algebra Mn (K). A brief presentation of PI-theory and some concepts of graph theory, such as the definition of Eulerian graphs, which are the basic elements of this work, were presented to make the text self- contained. We show two different proofs of the Amitsur-Levitzki theorem, the proof of Razmyslov and other due to Swan's theorem - an important result on Eulerian graphs. Finally, a similar result of the Amitsur-Levitzki's theorem for skew-symmetric matrices is proved using elements of graph theory. We emphasize that the understanding of the technique makes it possible to simplify many results and has been an important tool in the study of PI-algebras. / Neste trabalho apresentamos algumas aplicações de Teoria de Grafos em problemas envolvendo identidades polinomiais para a álgebra das matrizes Mn (K). Uma breve apresentação de PI-teoria e de alguns on eitos de Teoria de Grafos, como a de_- nição de grafos eulerianos, que são os elementos básicos desta abordagem, foram apresentadas para tornar o texto auto contido. São explicitadas duas demonstrações distintas do Teorema de Amitsur-Levitzki, a de Razmyslov e uma de corrente do Teorema de Swan - um resultado importante a respeito de grafos eulerianos. Por _m, um resultado semelhante ao Teorema de Amitsur-Levitzki para matrizes antis- simétricas é demonstrado utilizando elementos de Teoria de Grafos. Ressaltamos que o entendimento da técnica utilizada torna possível a simplificação de diversos resultados e tem se mostrado uma importante ferramenta no estudo de PI-álgebras.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-07-23T14:58:20Z No. of bitstreams: 1 LEOMAQUES FRANCISCO SILVA BERNARDO - DISSERTAÇÃO PPGMAT 2009..pdf: 656966 bytes, checksum: 9ca0422e8cc572aa2c43d542260ef401 (MD5) / Made available in DSpace on 2018-07-23T14:58:20Z (GMT). No. of bitstreams: 1 LEOMAQUES FRANCISCO SILVA BERNARDO - DISSERTAÇÃO PPGMAT 2009..pdf: 656966 bytes, checksum: 9ca0422e8cc572aa2c43d542260ef401 (MD5) Previous issue date: 2009-06 / Capes / Neste trabalho apresentamos um estudo sobre identidades e polinômios centrais para a álgebra das matrizes. Mais precisamente, apresentamos a descrição das identidades e polinômios centrais Zn-graduados e Z-graduados para a álgebra Mn(K) (matizes n x n sobre um corpo K), quando característica de K é zero. Depois, apresentamos a descrição dos polinômios centrais ordinários para a álgebra M2(K) (matrizes 2 x 2 sobre K), também para um corpo de característica zero. Finalmente, apresentamos duas construções clássicas de polinômios centrais para Mn(K), que surgiram como resposta a um problema sugerido por Kaplansky em 1956 sobre a existência de polinômios não triviais para esta álgebra. / In this work we study polynomial identities and central polynomials for matrix algebras. More precisely, we present the description of the identities and Zn-graded and Z-graded central polynomials for the algebra Mn(K) (the n x n matrices over the field K) when the characteristic of K is zero. Afterwards we give the description or the ordinary (nongraded) central polynomials for the algebra m2(K), the 2 x 2 matrices over K, assuming the field of characteristic zero. Finally, we present two classical constructions of central polynomials for Mn(K). These appeared as an answer to a problem posed by Kaplansky in 1956 about the existence of nontrivial central polynomials for that algebra.

<p>The Division of Computer Engineering at Linköping's university is currently researching the possibility to create a highly parallel DSP platform, that can keep up with the computational needs of upcoming standards for various applications, at low cost and low power consumption. The architecture is called ePUMA and it combines a general RISC DSP master processor with eight SIMD co-processors on a single chip. The master processor will act as the main processor for general tasks and execution control, while the co-processors will accelerate computing intensive and parallel DSP kernels.This thesis investigates the performance potential of the co-processors by implementing matrix algebra kernels for QR decomposition, LU decomposition, matrix determinant and matrix inverse, that run on a single co-processor. The kernels will then be evaluated to find possible problems with the co-processors' microarchitecture and suggest solutions to the problems that might exist. The evaluation shows that the performance potential is very good, but a few problems have been identified, that causes significant overhead in the kernels. Pipeline mismatches, that occurs due to different pipeline lengths for different instructions, causes pipeline hazards and the current solution to this, doesn't allow effective use of the pipeline. In some cases, the single port memories will cause bottlenecks, but the thesis suggests that the situation could be greatly improved by using buffered memory write-back. Also, the lack of register forwarding makes kernels with many data dependencies run unnecessarily slow.</p>