中文摘要：

针对损失数据线性参数系统的参数辨识问题,借助辅助模型辨识思想推导出其变递推间隔辅助模型递推最小二乘算法.为了提高该算法的计算效率,利用分解技术得到变递推间隔分解递推最小二乘算法估计系统参数.此外,在变递推间隔分解递推最小二乘算法中引入遗忘因子,从而提高参数估计精度和收敛速度.仿真结果表明,所提出的算法能有效估计系统参数.

英文摘要：

An interval-varying auxiliary model based recursive least squares（AM-RLS） algorithm is derived for linear-inparameter systems with missing data by means of the auxiliary model identification idea. In order to improve the computation efficiency, an interval-varying decomposition AM-RLS algorithm is proposed for estimating the system parameters. The introduction of the forgetting factors can improve the parameter estimation accuracy and accelerate the convergence rates of the interval-varying decomposition based AM-RLS algorithm. The simulation results show that the proposed algorithms can effectively estimate the parameters of the system.