Del 97 i serien IMA Volumes in Mathematics and its Applications

Random Sets

Theory and Applications

Inbunden, Engelska, 1997

AvJohn Goutsias,Ronald P.S. Mahler,Hung T. Nguyen

1 399 kr

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THIS IS BOTH PROMO TEXT AND BACK COVER COPY!!!!! The chapters in this volume are based on a scientific workshop on the "Applications and Theory of Random Sets". They address theoretical and applied aspects of this field in diverse areas of applications such as Image Modeling and Analysis, Information/Data Fusion, and Theoretical Statistics and Expert Systems. Emphasis is given to potential applications in engineering problems of practical intereSt. This volume is of interest to mathematicians, engineers and scientists who are interested in the potential application of random set theory to practical problems in imaging, information fusion, and expert systems.

Produktinformation

Utgivningsdatum1997-10-30
Mått155 x 235 x 28 mm
Vikt816 g
FormatInbunden
SpråkEngelska
SerieIMA Volumes in Mathematics and its Applications
Antal sidor416
Upplaga1997
FörlagSpringer-Verlag New York Inc.
ISBN9780387983455

Tillhör följande kategorier

I. Image Modeling and Analysis.- Morphological analysis of random sets. An introduction.- Statistical problems for random sets.- On estimating granulometric discrete size distributions of random sets.- Logical granulometric filtering in the signal-union-clutter model.- On optimal filtering of morphologically smooth discrete random sets and related open problems.- II. Information/Data Fusion and Expert Systems.- On the maximum of conditional entropy for upper/lower probabilities generated by random sets.- Random sets in information fusion. An overview.- Cramér-Rao type bounds for random set problems.- Random sets in data fusion. Multi-object state-estimation as a foundation of data fusion theory.- Extension of relational and conditional event algebra to random sets with applications to data fusion.- Belief functions and random sets.- III. Theoretical Statistics and Expert Systems.- Uncertainty measures, realizations and entropies.- Random sets in decision-making.- Random sets unify, explain, and aid known uncertainty methods in expert systems.- Laws of large numbers for random sets.- Geometric structure of lower probabilities.- Some static and dynamic aspects of robust Bayesian theory.- List of Participants.