Data Fusion Mathematics
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Data Fusion Mathematics: Theory and Practice

Data Fusion Mathematics: Theory and Practice


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About the Book

Fills the Existing Gap of Mathematics for Data FusionData fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in va

Table of Contents:
Introduction to Data Fusion Process. Statistics, Probability Models and Reliability: Towards Probabilistic Data Fusion. Fuzzy Logic and Possibility Theory-Based Fusion. Filtering, Target Tracking and Kinematic Data Fusion. Decentralized Data Fusion Systems. Component Analysis and Data Fusion. Image Algebra and Image Fusion. Decision Theory and Fusion. Wireless Sensor Networks and Multimodal Data Fusion. Soft Computing Approaches to Data Fusion. Automatic Data Fusion. Notes and Information on Data Fusion Software Tools.

About the Author :
Jitendra R. Raol received a BE and ME in electrical engineering from the MS University of Baroda, Vadodara in 1971 and 1973, respectively, and a PhD (in electrical and computer engineering) from McMaster University, Hamilton, Canada in 1986. He taught for two years at the MS University of Baroda before joining the National Aeronautical Laboratory in 1975. He retired in 2007 as Scientist G and head, flight mechanics and control division at CSIR-NAL. His main research interests are DF, system identification, state/parameter estimation, flight mechanics-flight data analysis, H-infinity filtering, ANNs, fuzzy systems, genetic algorithms, and soft technologies for robotics.

Review :
"An application's guide to sensor fusion - Raol's comprehensive yet succinct handling of the mathematical fundamentals of sensor fusion make this a reference source for every practitioner." —Ajith K. Gopal, The Council for Scientific and Industrial Research in South Africa "… comprehensively presents tools for data fusions. Initial two chapters cover basic of data fusion and state estimations, especially Bayesian framework. The rest of chapters deal with advance topics that include fuzzy-logic based design, centralized and decentralized strategies, and image fusion. I feel the content of the book will useful both academia and industry." —Dr. Mangal Kothari, Indian Institute of Technology Kanpur


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Product Details
  • ISBN-13: 9781040071755
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Language: English
  • ISBN-10: 1040071759
  • Publisher Date: 27 Aug 2015
  • Binding: Digital (delivered electronically)
  • Sub Title: Theory and Practice


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