In a focused, in-depth study, this book explores the mathematical tools used in this increasingly widespread and important technical field. It includes the theory, methods, and tools used for creating a synergy of the information acquired from multiple sources, sensors, databases, and direct information by humans. Researchers, scientists, and engineers working in the multi-sensor/data fusion area will find this book to be a valuable tool for design and analysis, especially in areas like aerospace engineering, defense systems, and environmental monitoring, where data fusion is critically important.…mehr
In a focused, in-depth study, this book explores the mathematical tools used in this increasingly widespread and important technical field. It includes the theory, methods, and tools used for creating a synergy of the information acquired from multiple sources, sensors, databases, and direct information by humans. Researchers, scientists, and engineers working in the multi-sensor/data fusion area will find this book to be a valuable tool for design and analysis, especially in areas like aerospace engineering, defense systems, and environmental monitoring, where data fusion is critically important.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
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.
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.
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