data fusion mathematics de raol jitendra (16 résultats)

Softcover. First Paperback Edition. Octavo, xv, xix, xxii, xxx, 570 pages. In Very Good condition. Spine red with black lettering. Paperback binding. Covers have mild wear with small tape mend to head rear joint edge and faint creases to rear tail fore edge. Text block has extremely light wear to the edges. Illustrated. First Paperback Edition. NOTE: Shelved in Netdesk Column H, ND-H. 1378669. FP New Rockville Stock.

Softcover. Etat : Fine. Leichte Abnutzungen; Gebogener Buchrücken. 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.

Paperback. Etat : Brand New. 504 pages. 9.25x6.14x1.34 inches. In Stock.

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Hardcover. Etat : new. Hardcover. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multitarget angleonly tracking, and multisensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications.This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multisensor data fusion area. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Etat : new. Hardcover. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multitarget angleonly tracking, and multisensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications.This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multisensor data fusion area. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Etat : New. pp. 590.

Hardcover. Etat : new. Hardcover. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multitarget angleonly tracking, and multisensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications.This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multisensor data fusion area. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Etat : New. pp. 590.

Hardcover. Etat : Brand New. 2nd edition. 716 pages. 9.18x6.12x9.21 inches. In Stock.

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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.