Fundamentals of Stochastic Filtering (Stochastic Modelling and Applied Probability, Band 60) - Softcover

Bain, Alan; Crisan, Dan

Softcover

ISBN 10: 1441926429 ISBN 13: 9781441926425

Verlag: Springer, 2010

Inhaltsangabe

The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices. The book is intended as a reference for graduate students and researchers interested in the field. It is also suitable for use as a text for a graduate level course on stochastic filtering (suitable exercises and solutions are included).

Über diesen Titel

Über die Autorin bzw. den Autor

Alan Bain is Professor of Innovation in Learning, Teaching and Technology at Charles Sturt University. He has led comprehensive organisational change processes in various educational contexts, including higher education institutions and schools. He has held appointments at the University of Western Australia and Lehigh University and is the recipient of multiple competitive Faculty, University, State and National awards for his leadership and innovation, teaching, and research in the United States and Australia.

Lucia Zundans-Fraser is currently the Acting Deputy Dean in the Faculty of Arts and Education at Charles Sturt University. She is the recipient of two national, and multiple institutional, teaching excellence awards and has led a comprehensive organisational change process in higher education. Her research examines higher education course and subject design, inclusive education legislation and policy, pre-service teachers and their understandings of inclusion, and the use of evidence-based pedagogies in education.

Von der hinteren Coverseite

The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods.

The book should provide sufficient background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices.

The book is intended as a reference for graduate students and researchers interested in the field. It is also suitable for use as a text for a graduate level course on stochastic filtering. Suitable exercises and solutions are included.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2010
• Sprache: Englisch
• ISBN 10: 1441926429
• ISBN 13: 9781441926425
• Einband: Taschenbuch
• Anzahl der Seiten: 404
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland