Titlebook: Random Sets; Theory and Applicati John Goutsias,Ronald P. S. Mahler,Hung T. Nguyen Book 1997 Springer Science+Business Media New York 1997

HERTZ

Cramér—Rao Type Bounds for Random Set Problemsy and equivalence classes of random sets. The second bound, however, does not use random sets, but rather it is based on symmetric polynomials An interesting and previously unexplored connection between random sets and symmetric polynomials at an abstract level is suggested. Apparently, the shortest

Injunction

Random Sets in Data Fusion Multi-Object State-Estimation as a Foundation of Data Fusion Theoryons of random sets. A general solution is described in several forms, including the one using the conditional Choquet’s capacity functional. This paper explores the possibility of the abstract formulation of multi-object state-estimation problems becoming a foundation of data fusion theory. Distribu

不安

Extension of Relational and Conditional Event Algebra to Random Sets with Applications to Data Fusio of well-defined individual “conditional” events in a single larger space extending the original unconditional one. These conditional events can then be combined logically before being evaluated. A major application of CEA is to data fusion problems, especially the testing of hypotheses concerning t

細(xì)絲

秘方藥

Jingoism

Critical

Proclaim

吸引力

Cramér—Rao Type Bounds for Random Set Problemsresting and previously unexplored connection between random sets and symmetric polynomials at an abstract level is suggested. Apparently, the shortest path between random sets and symmetric polynomials is through a Banach space.

Guaff豪情痛飲

Random Sets in Data Fusion Multi-Object State-Estimation as a Foundation of Data Fusion Theoryr explores the possibility of the abstract formulation of multi-object state-estimation problems becoming a foundation of data fusion theory. Distributed data processing among multiple “intelligent” processing nodes will also be briefly discussed as an important aspect of data fusion theory.