Detail publikace

Approximation of Battery Transfer Function Using Neural Network

CIPÍN, R. TOMAN, M. PROCHÁZKA, P. PAZDERA, I. MIKLÁŠ, J.

Originální název

Approximation of Battery Transfer Function Using Neural Network

Anglický název

Approximation of Battery Transfer Function Using Neural Network

Jazyk

en

Originální abstrakt

This paper deals with a mathematical description of an alkaline battery impedance dependence on frequency. This mathematical description is done in two different ways. In the first case, a general fractional transfer function is used and in the second case an artificial neural network is used. Both approaches are discussed and compared with real measurement.

Anglický abstrakt

This paper deals with a mathematical description of an alkaline battery impedance dependence on frequency. This mathematical description is done in two different ways. In the first case, a general fractional transfer function is used and in the second case an artificial neural network is used. Both approaches are discussed and compared with real measurement.

Dokumenty

BibTex


@inproceedings{BUT165875,
  author="Radoslav {Cipín} and Marek {Toman} and Petr {Procházka} and Ivo {Pazdera} and Ján {Mikláš}",
  title="Approximation of Battery Transfer Function Using Neural Network",
  annote="This paper deals with a mathematical description of an alkaline battery impedance dependence on frequency. This mathematical description is done in two different ways. In the first case, a general fractional transfer function is used and in the second case an artificial neural network is used. Both approaches are discussed and compared with real measurement.",
  booktitle="ECS",
  chapter="165875",
  doi="10.1149/09901.0351ecst",
  howpublished="online",
  number="1",
  year="2020",
  month="december",
  pages="351--356",
  type="conference paper"
}