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著名的递推遗忘因子算法（ＲＦＦＡ）可以用来辨识时变系统参数，具有良好的跟踪性能．本文借助于随机过程理论分析了ＲＦＦＡ的收敛性和稳定性，给出了参数用踪误差的上下界．
The famous recursive forgetting factor algorithm (RFFA) can be used to identify time-varying system parameters, with good tracking performance. This paper analyzes the convergence and stability of RFFA by means of stochastic process theory, and gives the upper and lower bounds of parameter tracking error.