Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4974857 | Journal of the Franklin Institute | 2014 | 9 Pages |
Abstract
This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudo-linear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Sheng Ding, Rui Ding, Erfu Yang,