Fuzzy Variable Structure Dynamic Bayesian Network Applying Target Recognition

The fuzzy variable structure dynamic Bayesian network is constructed, and a statistical method based on the sample information and a learning method of sample-free Bayesian network parameters is presented; then target recognition is realized according to network inference, finally, applying the traditional hard decision, The dynamic decision is performed based on the soft decision principles and the network parameters' update online is finished based on linear weighted theory. Compared with classical static Bayesian network for target recognition, this approach resolves such issues as the sequential relationship of evidences at different time slice and the network inference of constant random variables. At the same time, the method not only improves believe of target recognition but also shortens the convergence period and effectively resolves error recognition problem caused by association. In addition, the network parameters' update online is finished.