Tracking object's type changes with fuzzy based fusion rule
  In this paper the behavior of three combinational rules for
temporal/sequential attribute data fusion for target type estimation are
analyzed. The comparative analysis is based on: Dempster's fusion rule proposed
in Dempster-Shafer Theory; Proportional Conflict Redistribution rule no. 5
(PCR5), proposed in Dezert-Smarandache Theory and one alternative class fusion
rule, connecting the combination rules for information fusion with particular
fuzzy operators, focusing on the t-norm based Conjunctive rule as an analog of
the ordinary conjunctive rule and t-conorm based Disjunctive rule as an analog
of the ordinary disjunctive rule. The way how different t-conorms and t-norms
functions within TCN fusion rule influence over target type estimation
performance is studied and estimated.
