Abstract
At the very beginning, a new inferring method was proposed, which synthesized different observable parameters of target characters based on discrete dynamic Bayesian network model. After that, a new inferring algorithm of discrete dynamic Bayesian network was discussed. In succession, the discrete dynamic Bayesian network model based on target identification was established. Then, graphic model to mitigate the complexity of the application was applied. Finally, the simulation result shows that this method can synthesize different target characters, enable them amend each other with respect to different time-phrases and accordingly overcome the limitations of identifying target merely through a single pattern.
Original language | English |
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Pages (from-to) | 117-120+126 |
Journal | Xitong Fangzhen Xuebao / Journal of System Simulation |
Volume | 21 |
Issue number | 1 |
State | Published - 5 Jan 2009 |
Keywords
- Discrete dynamic Bayesian network
- Radiant point
- Target identification
- Uncertain inference