• DocumentCode
    607534
  • Title

    Design of wideband Wilkinson dividers using neural network

  • Author

    Tejmlova, L. ; Sebesta, J.

  • Author_Institution
    Dept. of Radio Electron., Brno Univ. of Technol., Brno, Czech Republic
  • fYear
    2013
  • fDate
    16-17 April 2013
  • Firstpage
    204
  • Lastpage
    208
  • Abstract
    This document is focused on design of symmetrical wideband splitters which are determined for distribution signals from one common source to two sinks. The ratio of minimal and maximal frequency of bandwidth is approximately about 0.43. That is exactly why this complex design of splitter represents wideband solution. This paper contains fundamental theory for designing wideband splitters and solution by using neural networks. The problem is defined by two input variables - values of frequency to define the frequency band. The neural network is set up to compute parameters of planar structure. Designed splitters were manufactured and measured. Obtained S parameters, such as transmission, isolation or reflections are discussed in the closing part of this paper.
  • Keywords
    S-parameters; neural nets; power dividers; S parameter; distribution signal; frequency band; neural network; planar structure parameter; symmetrical wideband splitter design; wideband Wilkinson divider design; Biological neural networks; Frequency conversion; Scattering parameters; Substrates; Training; Wideband; Neural Network; S-parameters; Ultra-wideband Power Splitter; Wilkinson Power Divider;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radioelektronika (RADIOELEKTRONIKA), 2013 23rd International Conference
  • Conference_Location
    Pardubice
  • Print_ISBN
    978-1-4673-5516-2
  • Type

    conf

  • DOI
    10.1109/RadioElek.2013.6530917
  • Filename
    6530917