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Uncertainty theories and multisensor data fusion / Alain Appriou.

By: Material type: TextTextSeries: Instrumentation and measurement seriesPublication details: Hoboken, NJ : ISTE Ltd/John Wiley and Sons Inc, 2014.Description: xiv, 262 p. : illustrations ; 24 cmISBN:
  • 9781848213548
Subject(s): DDC classification:
  • 623.042 23 Ap652
Contents:
Introduction-- 1. Multisensor data fusion-- 2. Reference formalisms-- 3. Set management and information propagation-- 4. Managing the reliability of information-- 5. Combination of sources-- 6. Data modeling-- 7. Classification: decision-making and exploitation of the diversity of information sources-- 8. Spatial dimension: data association-- 9. Temporal dimension: tracking-- Conclusion-- Bibliography-- Index.
Summary: Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessary? How can the available measurements be characterized in such a case? What is the purpose and the specificity of information fusion processing in multiple sensor systems? Considering the different uncertainty formalisms, a set of coherent operators corresponding to the different steps of a complete fusion process is then developed, in order to meet the requirements identified in the first part of the book.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 623.042 Ap652 (Browse shelf(Opens below)) Available 136428
Total holds: 0

Includes bibliographical references and index.

Introduction--
1. Multisensor data fusion--
2. Reference formalisms--
3. Set management and information propagation--
4. Managing the reliability of information--
5. Combination of sources--
6. Data modeling--
7. Classification: decision-making and exploitation of the diversity of information sources--
8. Spatial dimension: data association--
9. Temporal dimension: tracking--
Conclusion--
Bibliography--
Index.

Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessary? How can the available measurements be characterized in such a case? What is the purpose and the specificity of information fusion processing in multiple sensor systems? Considering the different uncertainty formalisms, a set of coherent operators corresponding to the different steps of a complete fusion process is then developed, in order to meet the requirements identified in the first part of the book.

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