Modeling of microwave filters using gradient Particle Swarm Optimization neural networks

Abstract

In this paper, hybrid algorithm called gradient particle swarm optimization (GPSO) is proposed for training artificial neural networks (ANN). Then, the trained networks are applied to modeling waveguide filters (broad-band e-plane filters with improved stop-band and rectangular waveguide h-plane three-cavity filter). For validate effectiveness of this algorithm, we compared the results of convergence and modeling obtained with those obtained by back- propagation neural networks (BP-NN) and particle swarm optimization neural networks (PSO-NN).