A Recursive Householder Transformation Method for Parameter Estimation of Difference Model
差分模型参数递推估计的Householder变换法

A new recursive Householder transformation method for parameter estimation of the difference model is proposed. Based on the new method, a series of new recursive algorithms, such as the new recursive least squares algorithm, the generalized least squares algorithm, the extended matrix algorithm, and the maximum likelihood algorithm are constructed. The new recursive least squares algorithms for both single and multiple variable cases and a comparison between these new algorithms and the traditional ones are discussed in detail. At last, several examples are given.