<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Kramers-Kronig (KK) equations allow us to obtain the real or imaginary part of linear, causal and time constant functions, starting from the imaginary or real part respectively. They are normally applied on different practical applications as a control method. A common problem in measurements is the lack of data in a wide-range frequency, due to some of the inherent limitations of experiments or practical limitations of the used technology. Different solutions to this problem were proved, such as several methods for extrapolation, some of which based on piecewise polynomial fit or the approach based on the expected asymptotical behavior. In this work, we propose an approach based on the symmetric extrapolation method to generate data in missing frequency ranges, to minimize the estimated error of the KK equations. The results show that with data from impedance measurements of an electrode-electrolyte interface, the adjustment error of the transformed functions can be drastically reduced to below 1%.</p></abstract>

Kramers-Kronig (KK) equations allow us to obtain the real or imaginary part of linear, causal and time constant functions, starting from the imaginary or real part respectively. They are normally applied on different practical applications as a control method. A common problem in measurements is the lack of data in a wide-range frequency, due to some of the inherent limitations of experiments or practical limitations of the used technology. Different solutions to this problem were proved, such as several methods for extrapolation, some of which based on piecewise polynomial fit or the approach based on the expected asymptotical behavior. In this work, we propose an approach based on the symmetric extrapolation method to generate data in missing frequency ranges, to minimize the estimated error of the KK equations. The results show that with data from impedance measurements of an electrode-electrolyte interface, the adjustment error of the transformed functions can be drastically reduced to below 1%.

Low error Kramers-Kronig estimations using symmetric extrapolation method

Journal of Electrical Bioimpedance

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Low error Kramers-Kronig estimations using symmetric extrapolation method"}

Kramers-Kronig (KK) equations allow us to obtain the real or imaginary part of linear, causal and time constant functions, starting from the imaginary or real...

Low error Kramers-Kronig estimations using symmetric extrapolation method

Data publikacji: 27 gru 2021

Zakres stron: 147 - 152

Otrzymano: 01 wrz 2021

DOI: https://doi.org/10.2478/joeb-2021-0017

Słowa kluczowe
Kramers-Kronig, symmetric, extrapolation

© 2021 Ruiz, G.A., Felice C.J., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Low error Kramers-Kronig estimations using symmetric extrapolation method

Data publikacji: 27 gru 2021

Zakres stron: 147 - 152

Otrzymano: 01 wrz 2021

DOI: https://doi.org/10.2478/joeb-2021-0017

Słowa kluczoweKramers-Kronig, symmetric, extrapolation

© 2021 Ruiz, G.A., Felice C.J., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Słowa kluczowe
Kramers-Kronig, symmetric, extrapolation