Convergence is a crucial issue in iterative algorithms. Damping is commonly employed to ensure the convergence of iterative algorithms. The conventional ways of damping are scalar-wise, and either heuristic or empirical. Recently, an analytically optimized vector damping was proposed for memory message-passing (iterative) algorithms. As a result, it yields a special class of covariance matrices called L-banded matrices. In this paper, we show these matrices have broad algebraic properties arising from their L-banded structure. In particular, compact analytic expressions for the LDL decomposition, the Cholesky decomposition, the determinant after a column substitution, minors, and cofactors are derived. Furthermore, necessary and sufficient conditions for an L-banded matrix to be definite, a recurrence to obtain the characteristic polynomial, and some other properties are given. In addition, we give new derivations of the determinant and the inverse.
翻译:收敛是迭代算法中的一个关键问题。阻尼通常被用来确保迭代算法的收敛性。传统的阻尼方式是逐个标量修改,要么是启发式的要么是经验性的。最近,针对内存传递(迭代)算法提出了一种经过分析优化的向量阻尼。因此,它产生了一类特殊的协方差矩阵,称为L-banded矩阵。在本文中,我们展示了这些矩阵由于其L-banded结构而具有广泛的代数性质。特别地,推导出了LDL分解、Cholesky分解、列换代后行列式、代数余子式的紧凑解析表达式。此外,给出了判定一个L-banded矩阵为正定矩阵所需的充分必要条件、用于计算特征多项式的递归方法和其他一些性质。此外,我们还提供了行列式和逆矩阵的新推导。