Uncertainty presents significant challenges in the reasoning about and controlling of complex dynamical systems. To address this challenge, numerous researchers are developing improved methods for stochastic analysis. This book presents a diverse collection of some of the latest research in this important area. In particular, this book gives an overview of some of the theoretical methods and tools for stochastic analysis, and it presents the applications of these methods to problems in systems theory, science, and economics
This course covers the basic models and solution techniques for problems of sequential decision maki...
In recent years, there has been a growing interest in developing statistical learning methods to pro...
This book presents the fundamental notions and advanced mathematical tools in the stochastic modelin...
Stochastic control plays an important role in many scientific and applied disciplines including comm...
Modeling techniques for uncertain systems has been a major research component of the Dynamic Systems...
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these sy...
A survey of two different methods for the analyses of uncertain dynamical systems is presented. As u...
Stochastic analysis has a variety of applications to biological systems as well as physical and engi...
This book provides a comprehensive presentation of classical and advanced topics in estimation and c...
This book is a result of many years of author's research and teaching on random vibration and contro...
Stochastic control theory is introduced and its importance relative to control science in general is...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
International audienceThis paper deals with a short overview on stochastic modeling of uncertainties...
This study applies generalized polynomial chaos theory to dynamic systems with uncertainties
The main objective of this book is to introduce the reader to the fundamentals of the area of probab...
This course covers the basic models and solution techniques for problems of sequential decision maki...
In recent years, there has been a growing interest in developing statistical learning methods to pro...
This book presents the fundamental notions and advanced mathematical tools in the stochastic modelin...
Stochastic control plays an important role in many scientific and applied disciplines including comm...
Modeling techniques for uncertain systems has been a major research component of the Dynamic Systems...
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these sy...
A survey of two different methods for the analyses of uncertain dynamical systems is presented. As u...
Stochastic analysis has a variety of applications to biological systems as well as physical and engi...
This book provides a comprehensive presentation of classical and advanced topics in estimation and c...
This book is a result of many years of author's research and teaching on random vibration and contro...
Stochastic control theory is introduced and its importance relative to control science in general is...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
International audienceThis paper deals with a short overview on stochastic modeling of uncertainties...
This study applies generalized polynomial chaos theory to dynamic systems with uncertainties
The main objective of this book is to introduce the reader to the fundamentals of the area of probab...
This course covers the basic models and solution techniques for problems of sequential decision maki...
In recent years, there has been a growing interest in developing statistical learning methods to pro...
This book presents the fundamental notions and advanced mathematical tools in the stochastic modelin...