Interpolation based on stationary and adaptive AR(1) modeling
Paper in proceeding, 2011

In this paper, we describe a minimal mean square error (MMSE) optimal interpolation filter for discrete random signals. We explicitly derive the interpolation filter for a first-order autoregressive process (AR(1)), and show that the filter depends only on the two adjacent points. The result is extended by developing an algorithm called local AR approximation (LARA), where a random signal is locally estimated as an AR(1) process. Experimental evaluation illustrates that LARA interpolation yields a lower mean square error than other common interpolation techniques, including linear, spline and local polynomial approximation (LPA).

Interpolation

LMMSE estimation

autoregressive modeling

adaptive filtering

Author

Eija Johansson

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Marie Ström

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Lennart Svensson

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Mats Viberg

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

15206149 (ISSN)

4052-4055 5947242
978-145770539-7 (ISBN)

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/ICASSP.2011.5947242

ISBN

978-145770539-7

More information

Created

10/7/2017