English

Periodic Chandrasekhar recursions

Methodology 2007-11-27 v1

Abstract

This paper extends the Chandrasekhar-type recursions due to Morf, Sidhu, and Kailath "Some new algorithms for recursive estimation in constant, linear, discrete-time systems, IEEE Trans. Autom. Control 19 (1974) 315-323" to the case of periodic time-varying state-space models. We show that the S-lagged increments of the one-step prediction error covariance satisfy certain recursions from which we derive some algorithms for linear least squares estimation for periodic state-space models. The proposed recursions may have potential computational advantages over the Kalman Filter and, in particular, the periodic Riccati difference equation.

Cite

@article{arxiv.0711.3857,
  title  = {Periodic Chandrasekhar recursions},
  author = {Abdelhakim Aknouche and Fayçal Hamdi},
  journal= {arXiv preprint arXiv:0711.3857},
  year   = {2007}
}
R2 v1 2026-06-21T09:46:56.030Z