一种具有特殊滤波器的递推极大似然法

A Recursive Maximum Likelihood Method with Special Filter

本文提出一种采用特殊滤滤器的递推极大似然法。该法不需单独估计滤波器的参数与阶次，而只需递推估计模型参数；其算法简单、计算量小、辨识精度高、收敛性好，并可用于在线辨识和实时数据处理。文中还通过计算机仿真与传统的参数辨识方法进行了分析比较。

A recursive maximum likelihood method with special filter [RML (SF)] is proposed. The parameters of filter in consequence of the computational method are simplified. The RML (SF) method is better than other traditional recursive methods in calculated consumption,estimated accuracy and convergency.It can be used in on-line identification and real-time data processing.It is also compared with the traditional parameter identification methods by computer digital simulation.