Download or read book Statistical Multisource multitarget Information Fusion written by Ronald P. S. Mahler and published by Artech House Publishers. This book was released on 2007 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive resource provides you with an in-depth understanding of finite-set statistics (FISST) ndash; a recently developed method which unifies much of information fusion under a single probabilistic, in fact Bayesian, paradigm. The book helps you master FISST concepts, techniques, and algorithms, so you can use FISST to address real-world challenges in the field. You learn how to model, fuse, and process highly disparate information sources, and detect and track non-cooperative individual/platform groups and conventional non-cooperative targets.

Download or read book Advances in Statistical Multisource Multitarget Information Fusion written by Ronald P.S. Mahler and published by Artech House. This book was released on 2014-08-01 with total page 1167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the sequel to the 2007 Artech House bestselling title, Statistical Multisource-Multitarget Information Fusion. That earlier book was a comprehensive resource for an in-depth understanding of finite-set statistics (FISST), a unified, systematic, and Bayesian approach to information fusion. The cardinalized probability hypothesis density (CPHD) filter, which was first systematically described in the earlier book, has since become a standard multitarget detection and tracking technique, especially in research and development. Since 2007, FISST has inspired a considerable amount of research, conducted in more than a dozen nations, and reported in nearly a thousand publications. This sequel addresses the most intriguing practical and theoretical advances in FISST, for the first time aggregating and systematizing them into a coherent, integrated, and deep-dive picture. Special emphasis is given to computationally fast exact closed-form implementation approaches. The book also includes the first complete and systematic description of RFS-based sensor/platform management and situation assessment.

Download or read book Information Theoretic Information Fusion written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Final Report summarizes research on information fusion based on finite-set statistics (FISST). FISST provides a fully unified, scientifically defensible, probabilistic foundation for the following aspects of multisource, multitarget, multiplatform data fusion: (1) multisource integration (detection, identification, and tracking) based on Bayesian filtering and estimation; (2) sensor management using control theory; (3) performance evaluation using information theory; (4) expert-systems theory (fuzzy logic, the Dempster-Shafer theory of evidence, rule-based inference); (5) distributed fusion; and (5) aspects of situation threat assessment. The core of FISST is a multisource-multitarget differential and integral calculus based on the fact that belief-mass functions are the multisensor-multitarget counterparts of probability-mass functions. One purpose of this calculus is to enable signal processing engineers to directly generalize conventional, engineering-friendly statistical reasoning to multisensor, multitarget, multi-evidence applications. A second purpose is to extend Bayesian (and other probabilistic) methodologies so that they are capable of dealing with (1) imperfectly characterized data and sensor models; and (2) two sensor models and true target models for multisource-multitarget problems. One consequence is that FlSST encompasses certain expert-system approaches that are often described as "heuristic"--Fuzzy logic, the Dempster-Shafer theory of evidence, and rule-based inference-as special cases of a single probabilistic paradigm. Section A and Appendix 1 of the report summarize FISST and its basic consequences. Section B summarizes progress made during the course of the contract. Section 0 summarizes our progress in transitioning this USARO-funded basic research into practical applied-research funded by other DoD agencies.

Download or read book Multiblock Data Fusion in Statistics and Machine Learning written by Age K. Smilde and published by John Wiley & Sons. This book was released on 2022-05-03 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiblock Data Fusion in Statistics and Machine Learning Explore the advantages and shortcomings of various forms of multiblock analysis, and the relationships between them, with this expert guide Arising out of fusion problems that exist in a variety of fields in the natural and life sciences, the methods available to fuse multiple data sets have expanded dramatically in recent years. Older methods, rooted in psychometrics and chemometrics, also exist. Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is a detailed overview of all relevant multiblock data analysis methods for fusing multiple data sets. It focuses on methods based on components and latent variables, including both well-known and lesser-known methods with potential applications in different types of problems. Many of the included methods are illustrated by practical examples and are accompanied by a freely available R-package. The distinguished authors have created an accessible and useful guide to help readers fuse data, develop new data fusion models, discover how the involved algorithms and models work, and understand the advantages and shortcomings of various approaches. This book includes: A thorough introduction to the different options available for the fusion of multiple data sets, including methods originating in psychometrics and chemometrics Practical discussions of well-known and lesser-known methods with applications in a wide variety of data problems Included, functional R-code for the application of many of the discussed methods Perfect for graduate students studying data analysis in the context of the natural and life sciences, including bioinformatics, sensometrics, and chemometrics, Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is also an indispensable resource for developers and users of the results of multiblock methods.

Download or read book Beetown Wisconsin 1827 1977 written by and published by . This book was released on 1977 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Fusion Concepts and Ideas written by H B Mitchell and published by Springer Science & Business Media. This book was released on 2012-02-09 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to the concepts and idea of multisensor data fusion. It is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction" which was originally published by Springer-Verlag in 2007. The main changes in the new book are: New Material: Apart from one new chapter there are approximately 30 new sections, 50 new examples and 100 new references. At the same time, material which is out-of-date has been eliminated and the remaining text has been rewritten for added clarity. Altogether, the new book is nearly 70 pages longer than the original book. Matlab code: Where appropriate we have given details of Matlab code which may be downloaded from the worldwide web. In a few places, where such code is not readily available, we have included Matlab code in the body of the text. Layout. The layout and typography has been revised. Examples and Matlab code now appear on a gray background for easy identification and advancd material is marked with an asterisk. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familarity with the basic tools of linear algebra, calculus and simple probability is recommended. Although conceptually simple, the study of mult-sensor data fusion presents challenges that are unique within the education of the electrical engineer or computer scientist. To become competent in the field the student must become familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory. All too often, the student views multi-sensor data fusion as a miscellaneous assortment of different processes which bear no relationship to each other. In contrast, in this book the processes are unified by using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references.

Download or read book Advances in Multi Sensor Information Fusion Theory and Applications 2017 written by Xue-Bo Jin and published by MDPI. This book was released on 2018-06-26 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Advances in Multi-Sensor Information Fusion: Theory and Applications 2017" that was published in Sensors

Download or read book Handbook of Multisensor Data Fusion written by Martin Liggins II and published by CRC Press. This book was released on 2017-01-06 with total page 870 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.

Download or read book Multisensor Data Fusion written by Hassen Fourati and published by CRC Press. This book was released on 2017-12-19 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multi Sensor Information Fusion written by Xue-Bo Jin and published by MDPI. This book was released on 2020-03-23 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Download or read book Context Enhanced Information Fusion written by Lauro Snidaro and published by Springer. This book was released on 2016-05-25 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text reviews the fundamental theory and latest methods for including contextual information in fusion process design and implementation. Chapters are contributed by the foremost international experts, spanning numerous developments and applications. The book highlights high- and low-level information fusion problems, performance evaluation under highly demanding conditions, and design principles. A particular focus is placed on approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective. Features: introduces the terminology and core elements in information fusion and context; presents key themes for context-enhanced information fusion; discusses design issues in developing context-aware fusion systems; provides mathematical grounds for modeling the contextual influences in representative fusion problems; describes the fusion of hard and soft data; reviews a diverse range of applications.

Download or read book Human Centered Information Fusion written by David Lee Hall and published by Artech House. This book was released on 2010 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information fusion refers to the merging of information from disparate sources with differing conceptual, contextual and typographical representations. Rather than focusing on traditional data fusion applications which have been mainly concerned with physical military targets, this unique resource explores new human-centered trends, such as locations, identity, and interactions of individuals and groups (social networks). Moreover, the book discusses two new major sources of information: human observations and web-based information.This cutting-edge volume presents a new view of multi-sensor data fusion that seeks to address these new developments, explicitly considering the active role of a human user/analyst. Professionals become knowledgeable about the key inputs into this innovative information fusion process, including traditional sensing resources (S-space), dynamic communities of human observers (H-space), and resources such as archived sensor data, blogs, and dynamic news reports from citizen reporters via the Internet (I-space).

Download or read book Distributed Data Fusion for Network Centric Operations written by David Hall and published by CRC Press. This book was released on 2017-12-19 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent proliferation of service-oriented architectures (SOA), cloud computing technologies, and distributed-interconnected systems, distributed fusion is taking on a larger role in a variety of applications—from environmental monitoring and crisis management to intelligent buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the state of the art of data fusion in a distributed sensing, communications, and computing environment. Get Insight into Designing and Implementing Data Fusion in a Distributed Network Addressing the entirety of information fusion, the contributors cover everything from signal and image processing, through estimation, to situation awareness. In particular, the work offers a timely look at the issues and solutions involving fusion within a distributed network enterprise. These include critical design problems, such as how to maintain a pedigree of agents or nodes that receive information, provide their contribution to the dataset, and pass to other network components. The book also tackles dynamic data sharing within a network-centric enterprise, distributed fusion effects on state estimation, graph-theoretic methods to optimize fusion performance, human engineering factors, and computer ontologies for higher levels of situation assessment. A comprehensive introduction to this emerging field and its challenges, the book explores how data fusion can be used within grid, distributed, and cloud computing architectures. Bringing together both theoretical and applied research perspectives, this is a valuable reference for fusion researchers and practitioners. It offers guidance and insight for those working on the complex issues of designing and implementing distributed, decentralized information fusion.

Download or read book Modern Approaches in Machine Learning and Cognitive Science A Walkthrough written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2020-02-04 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various machine learning & cognitive science approaches, presenting high-throughput research by experts in this area. Bringing together machine learning, cognitive science and other aspects of artificial intelligence to help provide a roadmap for future research on intelligent systems, the book is a valuable reference resource for students, researchers and industry practitioners wanting to keep abreast of recent developments in this dynamic, exciting and profitable research field. It is intended for postgraduate students, researchers, scholars and developers who are interested in machine learning and cognitive research, and is also suitable for senior undergraduate courses in related topics. Further, it is useful for practitioners dealing with advanced data processing, applied mathematicians, developers of software for agent-oriented systems and developers of embedded and real-time systems.

Download or read book Non Cooperative Target Tracking Fusion and Control written by Zhongliang Jing and published by Springer. This book was released on 2018-06-25 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.

Download or read book UAV Based Remote Sensing Volume 1 written by Felipe Gonzalez Toro and published by MDPI. This book was released on 2018-04-27 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "UAV-Based Remote Sensing" that was published in Sensors

Download or read book Target Tracking with Random Finite Sets written by Weihua Wu and published by Springer Nature. This book was released on 2023-08-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on target tracking and information fusion with random finite sets. Both principles and implementations have been addressed, with more weight placed on engineering implementations. This is achieved by providing in-depth study on a number of major topics such as the probability hypothesis density (PHD), cardinalized PHD, multi-Bernoulli (MB), labeled MB (LMB), d-generalized LMB (d-GLMB), marginalized d-GLMB, together with their Gaussian mixture and sequential Monte Carlo implementations. Five extended applications are covered, which are maneuvering target tracking, target tracking for Doppler radars, track-before-detect for dim targets, target tracking with non-standard measurements, and target tracking with multiple distributed sensors. The comprehensive and systematic summarization in target tracking with RFSs is one of the major features of the book, which is particularly suited for readers who are interested to learn solutions in target tracking with RFSs. The book benefits researchers, engineers, and graduate students in the fields of random finite sets, target tracking, sensor fusion/data fusion/information fusion, etc.