The matrix exponential is a very important subclass of functions of matrices that has been studied extensively in the last 50 years. In this thesis, we discuss some of the more common matrix functions and their general properties, and we specifically explore the matrix exponential. In principle, the matrix exponential could be computed in many ways. In practice, some of the methods are preferable to others, but none are completely satisfactory. Computations of the matrix exponential using Taylor Series, Scaling and Squaring, Eigenvectors, and the Schur Decomposition methods are provided.

Having origins in the increasingly popular Matrix Theory, the square root function of a matrix has received notable attention in recent years. In this thesis, we discuss some of the more common matrix functions and their general properties, but we specifically explore the square root function of a matrix and the most efficient method (Schur decomposition) of computing it. Calculating the square root of a 2×2 matrix by the Cayley-Hamilton Theorem is highlighted, along with square roots of positive semidefinite matrices and general square roots using the Jordan Canonical Form.

We propose a new framework for understanding block Krylov subspace methods, which hinges on a matrix-valued inner product. We can recast the ``classical" block Krylov methods, such as O'Leary's block conjugate gradients, global methods, and loop-interchange methods, within this framework. Leveraging the generality of the framework, we develop an efficient restart procedure and error bounds for the shifted block full orthogonalization method (Sh-BFOM(m)). Regarding BFOM as the prototypical block Krylov subspace method, we propose another formalism, which we call modified BFOM, and show that block GMRES and the new block Radau-Lanczos method can be regarded as modified BFOM. In analogy to Sh-BFOM(m), we develop an efficient restart procedure for shifted BGMRES with restarts (Sh-BGMRES(m)), as well as error bounds. Using this framework and shifted block Krylov methods with restarts as a foundation, we formulate block Krylov subspace methods with restarts for matrix functions acting on multiple vectors f(A)B. We obtain convergence bounds for \bfomfom (BFOM for Functions Of Matrices) and block harmonic methods (i.e., BGMRES-like methods) for matrix functions. With various numerical examples, we illustrate our theoretical results on Sh-BFOM and Sh-BGMRES. We also analyze the matrix polynomials associated to the residuals of these methods. Through a variety of real-life applications, we demonstrate the robustness and versatility of B(FOM)^2 and block harmonic methods for matrix functions. A particularly interesting example is the tensor t-function, our proposed definition for the function of a tensor in the tensor t-product formalism. Despite the lack of convergence theory, we also show that the block Radau-Lanczos modification can reduce the number of cycles required to converge for both linear systems and matrix functions. / Mathematics

Boolean functions are the main building blocks of most cipher systems. Various aspects of their cryptological characteristics are examined and investigated by many researchers from different fields. This thesis has no claim to obtain original results but consists in an attempt at giving a unified survey of the main results of the subject. In this thesis, the theory of boolean functions is presented in details, emphasizing some important cryptological properties such as balance, nonlinearity, strict avalanche criterion and propagation criterion. After presenting many results about these criteria with detailed proofs, two upper bounds and two lower bounds on the nonlinearity of a boolean function due to Zhang and Zheng are proved. Because of their importance in the theory of boolean functions, construction of Sylvester-Hadamard matrices are shown and most of their properties used in cryptography are proved. The Walsh transform is investigated in detail by proving many properties. By using a property of Sylvester-Hadamard matrices, the fast Walsh transform is presented and its application in finding the nonlinearity of a boolean function is demonstrated. One of the most important classes of boolean functions, so called bent functions, are presented with many properties and by giving several examples, from the paper of Rothaus. By using bent functions, relations between balance, nonlinearity and propagation criterion are presented and it is shown that not all these criteria can be simultaneously satisfied completely. For this reason, several constructions of functions optimizing these criteria which are due to Seberry, Zhang and Zheng are presented.

We present several methods that allow the exact computation of the exponential matrix etA. Methods that include computation of eigenvectors or Laplace transform are very well-known, and they are mentioned herefor completeness. We also present other methods, not well-known inthe literature, that do not need the computation of eigenvectors, and are easy to introduce in a classroom, thus providing us with general formulas that can be applied to any matrix. / Presentamos varios métodos que permiten el calculo exacto de la matriz exponencial etA. Los métodos que incluyen el calculo de autovectores y la transformada de Laplace son bien conocidos, y son mencionados aquí por completitud. Se mencionan otros métodos, no tan conocidos en la literatura, que no incluyen el calculo de autovectores, y que proveen de fórmulas genéricas aplicables a cualquier matriz.