Identification of Time Series Transfer Function Parmeter

DOI

10.2991/meic-14.2014.286How to use a DOI?

Keywords

transfer function models; frequency response function; identification procedure; least squares estimation; autocovariance function

Abstract

Transfer functions are commonly used in the analysis of systems such as single-input single-output filters, typically within the fields of signal processing, communication theory, and control theory. Transfer function models is of considerable interest in economics, engineering, biology, and many other fields. Models of this kind can describe not only the behavior of industrial processes but also that of economic and business systems. Transfer function model building is important because it is only when the dynamic characteristics of a system are understood that intelligent direction, manipulation, and control of the system is possible. Engineering methods for estimating transfer functions are usually based on the choice of special inputs to the system such as step and sine wave inputs and “pulse” inputs. These methods have been useful when the system is affected by small amounts of noise but are less satisfactory otherwise. In this paper we show procedure and methods for estimating the transfer function parameters.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Youxiang Cui
AU  - Bin Zhong
AU  - Weike Qian
AU  - Changjiang Zheng
PY  - 2014/11
DA  - 2014/11
TI  - Identification of Time Series Transfer Function Parmeter
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1272
EP  - 1275
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.286
DO  - 10.2991/meic-14.2014.286
ID  - Cui2014/11
ER  -