Efficient recursive least squares solver for rank-deficient matrices

作者：

Highlights：

• Derivation of rank-Greville algorithm, maintaining a general rank factorization.

• Exploiting rank-deficiency to reach an asymptotic computational complexity of O(mr) for updating a least-squares solution when adding an observation.

• Publically available implementation in Python3, using Numpy.

摘要

•Derivation of rank-Greville algorithm, maintaining a general rank factorization.•Exploiting rank-deficiency to reach an asymptotic computational complexity of O(mr) for updating a least-squares solution when adding an observation.•Publically available implementation in Python3, using Numpy.

论文关键词：Moore-Penrose pseudoinverse,Generalized inverse,Recursive least-squares,Rank-deficient linear systems

论文评审过程：Received 19 May 2020, Revised 26 December 2020, Accepted 9 January 2021, Available online 10 February 2021, Version of Record 10 February 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.125996