253 research outputs found

    On Functions of quasi Toeplitz matrices

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    Let a(z)=∑i∈Zaizia(z)=\sum_{i\in\mathbb Z}a_iz^i be a complex valued continuous function, defined for ∣z∣=1|z|=1, such that ∑i=−∞+∞∣iai∣<∞\sum_{i=-\infty}^{+\infty}|ia_i|<\infty. Consider the semi-infinite Toeplitz matrix T(a)=(ti,j)i,j∈Z+T(a)=(t_{i,j})_{i,j\in\mathbb Z^+} associated with the symbol a(z)a(z) such that ti,j=aj−it_{i,j}=a_{j-i}. A quasi-Toeplitz matrix associated with the continuous symbol a(z)a(z) is a matrix of the form A=T(a)+EA=T(a)+E where E=(ei,j)E=(e_{i,j}), ∑i,j∈Z+∣ei,j∣<∞\sum_{i,j\in\mathbb Z^+}|e_{i,j}|<\infty, and is called a CQT-matrix. Given a function f(x)f(x) and a CQT matrix MM, we provide conditions under which f(M)f(M) is well defined and is a CQT matrix. Moreover, we introduce a parametrization of CQT matrices and algorithms for the computation of f(M)f(M). We treat the case where f(x)f(x) is assigned in terms of power series and the case where f(x)f(x) is defined in terms of a Cauchy integral. This analysis is applied also to finite matrices which can be written as the sum of a Toeplitz matrix and of a low rank correction

    Efficient cyclic reduction for QBDs with rank structured blocks

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    We provide effective algorithms for solving block tridiagonal block Toeplitz systems with m×mm\times m quasiseparable blocks, as well as quadratic matrix equations with m×mm\times m quasiseparable coefficients, based on cyclic reduction and on the technology of rank-structured matrices. The algorithms rely on the exponential decay of the singular values of the off-diagonal submatrices generated by cyclic reduction. We provide a formal proof of this decay in the Markovian framework. The results of the numerical experiments that we report confirm a significant speed up over the general algorithms, already starting with the moderately small size m≈102m\approx 10^2

    A computational framework for two-dimensional random walks with restarts

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    The treatment of two-dimensional random walks in the quarter plane leads to Markov processes which involve semi-infinite matrices having Toeplitz or block Toeplitz structure plus a low-rank correction. Finding the steady state probability distribution of the process requires to perform operations involving these structured matrices. We propose an extension of the framework of [5] which allows to deal with more general situations such as processes involving restart events. This is motivated by the need for modeling processes that can incur in unexpected failures like computer system reboots. Algebraically, this gives rise to corrections with infinite support that cannot be treated using the tools currently available in the literature. We present a theoretical analysis of an enriched Banach algebra that, combined with appropriate algorithms, enables the numerical treatment of these problems. The results are applied to the solution of bidimensional Quasi-Birth-Death processes with infinitely many phases which model random walks in the quarter plane, relying on the matrix analytic approach. This methodology reduces the problem to solving a quadratic matrix equation with coefficients of infinite size. We provide conditions on the transition probabilities which ensure that the solution of interest of the matrix equation belongs to the enriched algebra. The reliability of our approach is confirmed by extensive numerical experimentation on some case studies
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