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New physics model and AI controllers for bowed-string instruments

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]

Read on arXiv cs.LG →

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New physics model and AI controllers for bowed-string instruments

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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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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Homayoon Beigi, Grace Conneely ·

    Learned Bow Control on a Measured Bowed-String Model: a Revised Minimum-Bow-Force Law, a Recurrent Controller, and the Domain of a Supervision Ceiling

    arXiv:2609.14990v1 Announce Type: cross Abstract: A finite-difference bowed-string model with implicitly resolved Stribeck friction is presented, with a regime diagnostic, the Schelleng bow-force limits on four strings, and a comparison of learned bow controllers. Implicit resolu…