Tracking of non-stationary biological signals with utilizing of adaptive filtering method

Autor:	Boris Rohal’-Ilkiv, Ludovit Malinovsky, Marek Honek, Karol Ondrejkovic
Rok vydání:	2015
Předmět:	Adaptive filter Noise Autoregressive model Noise measurement ComputingMethodologies_SIMULATIONANDMODELING Control theory Computer science Kalman filter Covariance intersection Covariance Tracking (particle physics) Algorithm
Zdroj:	2015 20th International Conference on Process Control (PC).
DOI:	10.1109/pc.2015.7169977
Popis:	This paper presents an approach intended for tracking of biological non-stationary signals. The proposed approach utilizes a Kalman filter autoregressive model together with a method for estimation of covariance matrices of the uncorrelated process noise and measurement noise. The method was tested in simulations, where the ability of tracking of a class of time varying autoregressive processes was the subject of our interest. The obtained results are promising in the meaning that the suggested algorithm is suitable to track the time varying autoregressive processes with sufficient accuracy.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5afa96c048889d0f7d63f56f0fcc9da2 https://doi.org/10.1109/pc.2015.7169977 Zobrazit plný text záznamu