This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures of such systems. It covers both retrospective and sequential problems, particularly theoretical methods of optimal detection. Such methods are constructed and their characteristics are analyzed both theoretically and experimentally.
Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.
Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.
"The objective of this book is to present theoretical and numerical results for detection and estimation of changes in complex systems. Retrospective and sequential detection of the change-points is considered. ...
I think that the book will be useful to many people because it presents the two types of change-point problems (retrospective and sequential), in various situations, presenting the theoretical results, simulations and real-world applications."
-Gabriela Ciuperca, in Mathematical Reviews Clippings, December 2017
I think that the book will be useful to many people because it presents the two types of change-point problems (retrospective and sequential), in various situations, presenting the theoretical results, simulations and real-world applications."
-Gabriela Ciuperca, in Mathematical Reviews Clippings, December 2017