This work is supported by the National Natural Science Foundation of China (No.60434020, No.60772006), Leading Academic Discipline Project of Shanghai Municipal Education Commission (No.J51901).
Many of large-scale systems have embraced a number of highly nonlinear dynamic behaviours and thus pose an operational challenge for fault diagnosis schemes based on a linear perturbation model. In this paper, we prop...
Supported by the NSFC (No. 60772006, 60874105);the ZJNSF (Y1080422, R106745);Aviation Science Foundation (20070511001)
Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledg...
Supports in part by the NSFC (No. 60772006, 60874105);the ZJNSF(Y1080422, R106745);NCET (08- 0345)
The original Probability Hypothesis Density (PHD) filter is a tractable algorithm for Multi-Target Tracking (MTT) in Random Finite Set (RFS) frameworks. In this paper,we introduce a novel Evidence PHD (E-PHD) filter w...