Neural Computation of Wide Aperture Dimension of Optimum Gain Pyramidal Horn

A new method based on the multilayered perceptron neural network architecture for computing the wide aperture dimension of the pyramidal horn is presented. The computed wide aperture dimension is used in successfully designing optimum gain pyramidal horn. The other design parameters of the horn are determined from the simple and explicit analytical formulas. These formulas do not need the application of the iterative methods, and are not restricted to the high gain horn designs. The gain of a designed pyramidal horn is determined with no path length error approximation. Better accuracy with respect to the previous design methods is obtained for various pyramidal horn design examples.