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To deal with the parameter estimation problem in multi-function radars( MFR) based on stochastic context-free grammar( SCFG) model,this paper developed a new method of MFR parameter estimation problem based on Earley parsing called EIO algorithm on the basis of traditional inside-outside( IO) algorithm and viterbi-score( VS) algorithm. This method pre-processed the intercepted radar data by combining IO algorithm with Earley parsing to handle arbitrary grammar production rules. It utilized the EIO algorithm to realize the learning of grammatical production rules probabilities and MFR parameter estimation. Theoretical analysis and simulation results show that the modified algorithm can reduce the computation complexity,memory complexity and running time while keeping the same level of estimation accuracy,validates the correctness and effectiveness of this method. [ABSTRACT FROM AUTHOR]

In this paper, a method for video events learning and recognition based-on key atomic actions is presented. First, the hierarchical structures of events and the temporal relations between sub-events and atomic actions are expressed by and-or graph, which is learned from training data by the minimum description length principle. Then, the weights of the atomic actions are computed according to their importance, and the atomic action with the maximum weight is regarded as the key atomic action. The weight values of the atomic actions could be used for real-time events parsing which leads to the improvement of event recognition ratio. We also define the event recognition degree based on the weight of atomic action to reduce the number of identified events and raise the efficiency of events recognition algorithm. Finally, the experimental results show that, in a variety of scenes, the proposed method is effective for event recognition. [ABSTRACT FROM AUTHOR]