Statistical Linearization and Consistent Measures of Dependence: A Unified Approach

Kirill Chernyshov

2015

Abstract

The paper presents a unified approach to the statistical linearization of input/output mapping of non-linear discrete-time stochastic systems driven with white-noise Gaussian process. The approach is concerned with a possibility of applying any consistent measures of dependence (that is those measures of dependence of a pair of random values, which vanish if and only if these random values are stochastically independent) in statistical linearization problems and oriented to the elimination of drawbacks concerned with applying correlation and dispersion (based on the correlation ratio) measures of dependence, based on linearized representations of their input/output models.

Paper Citation

in Harvard Style

Chernyshov K. (2015). Statistical Linearization and Consistent Measures of Dependence: A Unified Approach . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 524-532. DOI: 10.5220/0005534805240532

in Bibtex Style

@conference{icinco15,
author={Kirill Chernyshov},
title={Statistical Linearization and Consistent Measures of Dependence: A Unified Approach},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={524-532},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005534805240532},
isbn={978-989-758-122-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Statistical Linearization and Consistent Measures of Dependence: A Unified Approach
SN - 978-989-758-122-9
AU - Chernyshov K.
PY - 2015
SP - 524
EP - 532
DO - 10.5220/0005534805240532