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Enhanced neural modeling of planar antennas and filters

The paper deals with an enhanced neural modeling algorithm based on incorporation of both, global optimization method and local one. Proposed algorithm depresses disadvantages of classical neural modeling. A neural model of the low-pass filter is trained to behave as a numerical one, which is analyzed in Zeland IE3D. Both, the neural model and the numerical one are optimized using particle swarm optimization method (PSO). Finally, the results of optimization are compared.