Given the square matrices A,B,D,E and the matrix C of conforming dimensions, we consider
the linear matrix equation A\mathbfXE+D\mathbfXB=C in the unknown matrix \mathbfX. Our …

The theory of optimal control systems has grown and flourished since the 1960's. Many texts,
written on varying levels of sophistication, have been published on the subject. Yet even …

If a system and its observation are both represented in state space with linear equations, the
system noise and the measurement noise are white, Gaussian, and mutually uncorrelated …

Revised and updated, this second edition of Walter Gautschi's successful Numerical
Analysis explores computational methods for problems arising in the areas of classical …

The Handbook of Linear Algebra provides comprehensive coverage of linear algebra
concepts, applications, and computational software packages in an easy-to-use handbook …

Machine learning allows computers to learn and discern patterns without actually being
programmed. When Statistical techniques and machine learning are combined together they …

The FEniCS Project set out in 2003 with an idea to automate the solution of mathematical
models based on differential equations. Initially, the FEniCS Project consisted of two …

In this paper we present the cyclic low-rank Smith method, which is an iterative method for
the computation of low-rank approximations to the solution of large, sparse, stable Lyapunov …

We study large‐scale, continuous‐time linear time‐invariant control systems with a sparse or
structured state matrix and a relatively small number of inputs and outputs. The main …

This monograph aims to provide a concise and comprehensive treatment of the basic theory
of algebraic Riccati equations and a description of both the classical and the more advanced …