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Multisensor data fusion : from algorithms and architectural - download pdf or read online

By Hassen Fourati

ISBN-10: 1482263750

ISBN-13: 9781482263756

Multisensor facts Fusion: From Algorithms and Architectural layout to Applications covers the modern thought and perform of multisensor facts fusion, from primary techniques to state-of-the-art thoughts drawn from a vast array of disciplines. that includes contributions from the world’s top info fusion researchers and academicians, this authoritative book:

  • Presents cutting-edge advances within the layout of multisensor information fusion algorithms, addressing matters regarding the character, position, and computational skill of the sensors
  • Describes new fabrics and achievements in optimum fusion and multisensor filters
  • Discusses the benefits and demanding situations linked to multisensor info fusion, from prolonged spatial and temporal assurance to imperfection and variety in sensor technologies
  • Explores the topology, verbal exchange constitution, computational assets, fusion point, ambitions, and optimization of multisensor facts fusion process architectures
  • Showcases functions of multisensor facts fusion in fields corresponding to medication, transportation's site visitors, protection, and navigation

Multisensor information Fusion: From Algorithms and Architectural layout to Applications is a sturdy selection of sleek multisensor info fusion methodologies. The e-book instills a deeper realizing of the fundamentals of multisensor info fusion in addition to a realistic wisdom of the issues that may be confronted in the course of its execution.

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Multisensor data fusion : from algorithms and architectural - download pdf or read online

Multisensor facts Fusion: From Algorithms and Architectural layout to functions covers the modern thought and perform of multisensor info fusion, from primary thoughts to state of the art ideas drawn from a huge array of disciplines. that includes contributions from the world’s prime info fusion researchers and academicians, this authoritative book:Presents state of the art advances within the layout of multisensor info fusion algorithms, addressing concerns regarding the character, place, and computational skill of the sensorsDescribes new fabrics and achievements in optimum fusion and multisensor filtersDiscusses the benefits and demanding situations linked to multisensor facts fusion, from prolonged spatial and temporal assurance to imperfection and variety in sensor technologiesExplores the topology, verbal exchange constitution, computational assets, fusion point, ambitions, and optimization of multisensor info fusion procedure architecturesShowcases purposes of multisensor information fusion in fields corresponding to medication, transportation's site visitors, security, and navigationMultisensor facts Fusion: From Algorithms and Architectural layout to functions is a strong selection of glossy multisensor info fusion methodologies.

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Extra resources for Multisensor data fusion : from algorithms and architectural design to applications

Sample text

As a result, we explore data fusion algorithms according to a data-centric taxonomy [34]. 2 illustrates an overview of data-related challenges that are typically tackled by data fusion algorithms. The input data to the fusion system may be imperfect, correlated, inconsistent, and/or in disparate forms/modalities. 2 and discussed in the following. Various classifications of imperfect data have been proposed in the literature [35–37]. Our classification of imperfect data is inspired by the pioneering work of Smets’ [36] as well as an elaboration by Dubois and Prade [38].

IEEE European Simulation Interoperability Workshop, Genoa, Italy, June 2007. 20. U. Schade, J. Biermann, M. Frey and K. Kruger, From Battle Management Language (BML) to auto­ matic information fusion. Proceedings of Information Fusion & Geographic Information Systems (GIS), 2007, pp. 84–95. 21. H. Lee and B. P. Zeigler, SES-based ontological process for high level information fusion. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 7(4), Art. No. 129, 2010.

Parviz, Probability-possibility transformations: A comparison. International Journal of General Systems, 21(1):291–310, 1992. D. Dubois and H. Prade, Unfair coins and necessity measures: A possibilistic interpretation of histo­ grams. Fuzzy Sets and Systems, 10:15–20, 1983. G. Gross, R. Nagi and K. Sambhoos, A fuzzy graph matching approach in intelligence analysis and maintenance of continuous situational awareness. Journal of Information Fusion, 18:43–61, 2014. 15. D. L. Hall and J. Llinas, Handbook of Multisensor Data Fusion.

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Multisensor data fusion : from algorithms and architectural design to applications by Hassen Fourati


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