Adaptive neuro-fuzzy inference system for the computation of the characteristic impedance and the effective permittivity of the micro-coplanar strip line

Abstract

A method based on adaptive neuro-fuzzy inference system (ANFIS) for computing the effective permittivity and the characteristic impedance of the micro-coplanar strip (MCS) line is presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems (FISs). A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The effective permittivity and the characteristic impedance results obtained by using ANFIS are in good agreement with the theoretical and experimental results reported elsewhere.