{"ID":2854206,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.15796","arxiv_id":"2510.15796","title":"Cavity Duplexer Tuning with 1d Resnet-like Neural Networks","abstract":"This paper presents machine learning method for tuning of cavity duplexer with a large amount of adjustment screws. After testing we declined conventional reinforcement learning approach and reformulated our task in the supervised learning setup. The suggested neural network architecture includes 1d ResNet-like backbone and processing of some additional information about S-parameters, like the shape of curve and peaks positions and amplitudes. This neural network with external control algorithm is capable to reach almost the tuned state of the duplexer within 4-5 rotations per screw.","short_abstract":"This paper presents machine learning method for tuning of cavity duplexer with a large amount of adjustment screws. After testing we declined conventional reinforcement learning approach and reformulated our task in the supervised learning setup. The suggested neural network architecture includes 1d ResNet-like backbon...","url_abs":"https://arxiv.org/abs/2510.15796","url_pdf":"https://arxiv.org/pdf/2510.15796v1","authors":"[\"Anton Raskovalov\"]","published":"2025-10-17T16:16:56Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"eess.SY\"]","methods":"[\"Reinforcement Learning\"]","has_code":false}