Detail publikace

The Distributed Convergence Classifier Using the Finite Difference

KENYERES, M. KENYERES, J. ŠKORPIL, V.

Originální název

The Distributed Convergence Classifier Using the Finite Difference

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

The paper presents a novel distributed classifier of the convergence, which allows to detect the convergence/the divergence of a distributed converging algorithm. Since this classifier is supposed to be primarily applied in wireless sensor networks, its proposal makes provision for the character of these networks. The classifier is based on the mechanism of comparison of the forward finite differences from two consequent iterations. The convergence/the divergence is classifiable only in terms of the changes of the inner states of a particular node and therefore, no message redundancy is required for its proper functionality.

Klíčová slova

Distributed computing, wireless sensor networks, average consensus, distributed classifier

Autoři

KENYERES, M.; KENYERES, J.; ŠKORPIL, V.

Vydáno

1. 4. 2016

ISSN

1210-2512

Periodikum

Radioengineering

Ročník

25

Číslo

1

Stát

Česká republika

Strany od

148

Strany do

155

Strany počet

9

BibTex

@article{BUT122510,
  author="Martin {Kenyeres} and Jozef {Kenyeres} and Vladislav {Škorpil}",
  title="The Distributed Convergence Classifier Using the Finite Difference",
  journal="Radioengineering",
  year="2016",
  volume="25",
  number="1",
  pages="148--155",
  doi="10.13164/re.2016.0148",
  issn="1210-2512"
}