Linear stochastic systems are successfully used to provide mathematical models for real processes. This book covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations.

Covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations Includes detailed treatment of the fundamental properties of stochastic systems subjected both to multiplicative white noise and to jump Markovian perturbations Systematic presentation leads the reader in a natural way to the original results New theoretical results accompanied by detailed numerical examples Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations

Inhalt
Preliminaries to Probability Theory and Stochastic Differential Equations.- Exponential Stability and Lyapunov-Type Linear Equations.- Structural Properties of Linear Stochastic Systems.- The Riccati Equations of Stochastic Control.- Linear Quadratic Control Problem for Linear Stochastic Systems.- Stochastic Version of the Bounded Real Lemma and Applications.- Robust Stabilization of Linear Stochastic Systems.