Least-squares parameter estimation for systems with irregularly missing data

作者：Ding, Feng^*; Ding, Jie

来源：International Journal of Adaptive Control and Signal Processing, 2010, 24(7): 540-553.

DOI：10.1002/acs.1141

• signal processing
• parameter estimation
• missing data
• identification
• output estimation
• multirate systems
• least squares
• convergence properties
• irregular observations
• auxiliary models

This paper considers the problems of parameter identification and output estimation with possibly irregularly missing output data, using output error models. By means of an auxiliary model (or reference model) approach, we present a recursive least-squares algorithm to estimate the parameters of missing data systems, and establish convergence properties for the parameter and missing output estimation in the stochastic framework. The basic idea is to replace the unmeasurable inner variables with the output of an auxiliary model. Finally, we test the effectiveness of the algorithm with an example system.

• 出版日期2010-7
• 单位江南大学