Multi-Sensor Data Fusion: An Introduction
Author:   H.B. Mitchell
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of hardcover 1st ed. 2007
ISBN:  

9783642090677


Pages:   282
Publication Date:   15 October 2010
Replaced By:   9783642437304
Format:   Paperback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Multi-Sensor Data Fusion: An Introduction


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Overview

This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.

Full Product Details

Author:   H.B. Mitchell
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 2007
Dimensions:   Width: 15.50cm , Height: 1.50cm , Length: 23.50cm
Weight:   0.456kg
ISBN:  

9783642090677


ISBN 10:   3642090672
Pages:   282
Publication Date:   15 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Replaced By:   9783642437304
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Basics.- Sensors.- Architecture.- Representation.- Common Representational Format.- Spatial Alignment.- Temporal Alignment.- Sensor Value Normalization.- Data Fusion.- Bayesian Inference.- Parameter Estimation.- Robust Statistics.- Sequential Bayesian Inference.- Bayesian Decision Theory.- Ensemble Learning.- Sensor Management.- Sensor Management.- Appendices.- Software Sources.- Sensor Management.

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