This book develops methods for describing random dynamical systems, and it illustrats how the methods can be used in a variety of applications.
Appeals to researchers and graduate students who require tools to investigate stochastic systems.

Beginning with realistic mathematical or verbal models of physical or biological phenomena, the author derives tractable models for further mathematical analysis or computer simulations. For the most part, derivations are based on perturbation methods, and the majority of the text is devoted to careful derivations of implicit function theorems, the method of averaging, and quasi-static state approximation methods. The duality between stability and perturbation is developed and used, relying heavily on the concept of stability under persistent disturbances. Relevant topics about linear...