Sensor and Data Fusion

Sensor and Data Fusion
Author: Lawrence A. Klein
Publsiher: SPIE Press
Total Pages: 346
Release: 2004
Genre: Technology & Engineering
ISBN: 0819454354

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This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.

Fuzzy Logic and Information Fusion

Fuzzy Logic and Information Fusion
Author: Tomasa Calvo Sánchez,Joan Torrens Sastre
Publsiher: Springer
Total Pages: 242
Release: 2016-05-10
Genre: Technology & Engineering
ISBN: 9783319304212

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This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.

Quantitative Information Fusion for Hydrological Sciences

Quantitative Information Fusion for Hydrological Sciences
Author: Xing Cai,T.-C. Jim Yeh
Publsiher: Springer
Total Pages: 218
Release: 2008-01-12
Genre: Science
ISBN: 9783540753841

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In this rapidly evolving world of knowledge and technology, do you ever wonder how hydrology is catching up? Here, two highly qualified scientists edit a volume that takes the angle of computational hydrology and envision one of the science’s future directions – namely, the quantitative integration of high-quality hydrologic field data with geologic, hydrologic, chemical, atmospheric, and biological information to characterize and predict natural systems in hydrological sciences.

Multi Sensor Data Fusion with MATLAB

Multi Sensor Data Fusion with MATLAB
Author: Jitendra R. Raol
Publsiher: CRC Press
Total Pages: 570
Release: 2009-12-16
Genre: Technology & Engineering
ISBN: 9781439800058

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Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly

Sensor and Data Fusion Concepts and Applications

Sensor and Data Fusion Concepts and Applications
Author: Lawrence A. Klein
Publsiher: SPIE-International Society for Optical Engineering
Total Pages: 256
Release: 1999
Genre: Technology & Engineering
ISBN: STANFORD:36105021737866

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First published in 1993, this Tutorial Text has been revised and updated to provide explanations and examples of data fusion algorithms in areas not covered in the first edition. These include Bayesian inference, artificial neural networks and fuzzy logic. All of the chapters in the first edition have been revised and updated and new material is included on the FASCODE and MODTRAN atmospheric models, and EOSAEL, which analyzes physical processes that affect the performance of millimeter-wave and IR sensors.

Adaptive Modelling Estimation and Fusion from Data

Adaptive Modelling  Estimation and Fusion from Data
Author: Chris Harris,Xia Hong,Qiang Gan
Publsiher: Springer Science & Business Media
Total Pages: 334
Release: 2012-10-05
Genre: Computers
ISBN: 9783642182426

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This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.

Data Fusion Mathematics

Data Fusion Mathematics
Author: Jitendra R. Raol
Publsiher: CRC Press
Total Pages: 572
Release: 2015-08-27
Genre: Mathematics
ISBN: 9781498721028

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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

Multisensor Data Fusion

Multisensor Data Fusion
Author: Hassen Fourati
Publsiher: CRC Press
Total Pages: 639
Release: 2017-12-19
Genre: Technology & Engineering
ISBN: 9781482263756

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Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world’s leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.