Filtering of the ARMAX process with generalized t -distribution noise : the influence function approach
Ho, Weng Khuen
Ling, Keck Voon
Vu, Hoang Dung
Date of Issue2014
School of Electrical and Electronic Engineering
The commonly made assumption of Gaussian noise is an approximation to reality. In this paper, influence function, an analysis tool in robust statistics, is used to formulate a recursive solution for the filtering of the ARMAX process with generalized t-distribution noise. By being a superset encompassing Gaussian, uniform, t, and double exponential distributions, generalized t-distribution has the flexibility of characterizing noise with Gaussian or non-Gaussian statistical properties. The filter is formulated as a maximum likelihood problem, but instead of solving the optimization problem numerically, influence function approximation is used to obtain a recursive solution to reduce the computational load and facilitate real-time implementation. The influence function equations derived are also useful in determining the variance of the filter and the impact of outliers.
DRNTU::Engineering::Electrical and electronic engineering
Industrial & engineering chemistry research
© 2014 American Chemical Society. This is the author created version of a work that has been peer reviewed and accepted for publication by Industrial & Engineering Chemistry Research, American Chemical Society. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.1021/ie401990x].