Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation

Maciej Niedzwiecki; Marcin Ciolek

ICASSP 2018accepted0 citations

Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation

Abstract

The problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.

BibTeX

@inproceedings{icassp2018_twostageidentifi,
  title = {Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation},
  author = {Maciej Niedzwiecki and Marcin Ciolek},
  booktitle = {ICASSP 2018},
  year = {2018}
}