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
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;
Conference_Titel :
Radioelektronika (RADIOELEKTRONIKA), 2013 23rd International Conference
Conference_Location :
Pardubice
Print_ISBN :
978-1-4673-5516-2
DOI :
10.1109/RadioElek.2013.6530917