Bayes结构递归算法在目标类型和属性融合中的应用

摘要

By using Bayes structure recursive algorithm, this paper presents an example of how to combine the target type with the attribution measurements. Through the variance of each measurement during a certain time period, the target type and attribution probabilities are computed by using Bayes structure recursive algorithm. After multiple recursive computation, the probabilities are going to be stable, therefore the target type and attribution are determined.%应用Bayes结构递归算法，对一个目标类型和属性融合的应用实例进行计算。通过一定时间间隔的每一次测量值的变化，用Bayes算法计算目标类型和属性的概率值，多次递归计算后，概率值趋向于稳定，从而判定目标类型和属性。