Activation of the hidden layers of the modules are performed by the tangential-sigmoid type of function while the output layers are activated linearly. Briefly, the outputs of these ANN modules are the standing waves and the impedance transformation, which are the characteristic features of the transmission line circuits. The ANN architecture is also simple, which consists of the two simple multilayer perceptron (MLP) modules with the common inputs which are the termination Zs = Rs + jXs, line operation bandwidth B between the defined fmin, fmax and the dielectric e. Data ensembles for the training and testing processes are obtained from the systematically selected locations on the Smith chart with the adaptive radius sampling algorithm. Thus, relative to the similar works in the existing literature, this article provides the continuous Smith chart domain to facilitate the ‘‘Smith chart’’ methodology in solving the highly nonlinear transformation equations between the rectangular impedance and polar reflection planes for an infinite number of passive impedance to be used in design tasks of the microwave circuits. In this article, briefly the Smith chart is mapped with an artificial neural network (ANN) covering its whole details to be exploited CAD of the microwave circuitry.
