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Data Fusion Mathematics: Theory and Practice by Jitendra R. Raol (Paperback, 2017)

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Fills the Existing Gap of Mathematics for Data Fusion Data 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 various applications that include the monitoring of vehicles, aerospace systems, large-scale structures, and large industrial automation plants. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion, and provides a proper and adequate understanding of the basic mathematics directly related to DF. The material covered can be used for evaluation of the performances of any designed and developed DF systems. It tries to answer whether unified data fusion mathematics can evolve from various disparate mathematical concepts, and highlights mathematics that can add credibility to the data fusion process. Focuses on Mathematical Tools That Use Data Fusion This text explores the use of statistical/probabilistic signal/image processing, filtering, component analysis, image algebra, decision making, and neuro-FL-GA paradigms in studying, developing and validating data fusion processes (DFP). It covers major mathematical expressions, and formulae and equations as well as, where feasible, their derivations. It also discusses SDF concepts, DF models and architectures, aspects and methods of type 1 and 2 fuzzy logics, and related practical applications. In addition, the author covers soft computing paradigms that are finding increasing applications in multisensory DF approaches and applications. This book: Explores the use of interval type 2 fuzzy logic and ANFIS in DF Covers the mathematical treatment of many types of filtering algorithms, target-tracking methods, and kinematic DF methods Presents single and multi-sensor tracking and fusion mathematics Considers specific DF architectures in the context of decentralized systems Discusses information filtering, Bayesian approaches, several DF rules, image algebra and image fusion, decision fusion, and wireless sensor network (WSN) multimodality fusion Data Fusion Mathematics: Theory and Practice incorporates concepts, processes, methods, and approaches in data fusion that can help you with integrating DF mathematics and achieving higher levels of fusion activity, and clarity of performance. This text is geared toward researchers, scientists, teachers and practicing engineers interested and working in the multisensor data fusion area.

Product Identifiers

Publisher
Taylor & Francis Ltd
ISBN-13
9781138748637
eBay Product ID (ePID)
237321264

Product Key Features

Author
Jitendra R. Raol
Publication Name
Data Fusion Mathematics: Theory and Practice
Format
Paperback
Language
English
Subject
Engineering & Technology, Computer Science, Mathematics
Publication Year
2017
Type
Textbook
Number of Pages
504 Pages

Dimensions

Item Height
234mm
Item Width
156mm
Item Weight
839g

Additional Product Features

Title_Author
Jitendra R. Raol
Country/Region of Manufacture
United Kingdom

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Data Fusion Mathematics: Theory and Practice by Jitendra R. Raol (Paperback, 2017)

About this product

Product Information

Product Identifiers

Product Key Features

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Additional Product Features

Best Selling in Textbooks

Desk Reference to the Diagnostic Criteria from DSM-5-TR by American Psychiatric Association (2022, Trade Paperback)

PMBOK® Guide Ser.: Guide to the Project Management Body of Knowledge (PMBOK Guide) and the Standard for Project Management by Project Management Institute (2021, Trade Paperback)

Diagnostic and Statistical Manual of Mental Disorders DSM-5-TR by American Psychiatric Association (2022, Trade Paperback)

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