Adaptive Synthesis Using Hybrid Genetic Algorithm and Particle Swarm Optimization for Reflectionless Filter With Lumped Elements

In this article, an adaptive synthesis based on the hybrid genetic algorithm and particle swarm optimization (HGAPSO) is proposed for reflectionless filter design with lumped capacitors, resistors, inductors. The starts a preset topology, where each branch of topology represents small passive network elements. HGAPSO used to trim branches obtain proper values elements required filtering response. Focus model, embedded local searching policies random coordinate neighborhood search improve its ability. Besides, classifier-based strategy probabilistic method are introduced accelerate convergence boost iteration. Suitable topologies component determined automatically by meet specific To predict response accurately, EM-simulated result corresponding layout parasitic parameter models considered during fine-tuning. Based mechanisms mentioned above, four bandpass filters (BPFs) synthesized validate effectiveness procedure. fabricated exhibit good selectivity low reflection coefficient in measurement.