Researchers have developed a new finite-difference model for bowed-string instruments that incorporates an implicitly resolved Stribeck friction model. This model accurately captures the Schelleng bow-force limits and achieves a high stick fraction across four strings. The study also compares various learned bow controllers, finding that a gated recurrent network performed best, though it did not surpass a lookup rule for generating labels. AI
RANK_REASON The cluster contains a research paper published on arXiv detailing a new physics model and AI controllers for bowed-string instruments. [lever_c_demoted from research: ic=1 ai=0.7]
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