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Characteristic impedance calculation of CMOS synthetic transmission line using adaptive neuro-fuzzy inference system

For the design of the guiding properties of the synthetic transmission line so-called complementary-conducting-strip transmission lines (CCS TLs), full wave simulation tools are used. The characteristic impedance of the CCS TL is obtained from the scattering parameters generated by the simulation tools with considerable computational time. In this paper, the fuzzy neural network is used for helping the design of characteristic impedance. An adaptive neuro-fuzzy inference system is constructed to calculate the characteristic impedance corresponding to the input geometry parameters. The root mean square error between the result and the testing data generated from ANSYS− HFSS is 0.098 Ω.