{"paper":{"title":"Automated Pattern Detection--An Algorithm for Constructing Optimally Synchronizing Multi-Regular Language Filters","license":"","headline":"","cross_cats":["cond-mat.stat-mech","cs.CL","cs.DS","cs.IR","cs.LG","nlin.AO","nlin.CG","nlin.PS","physics.comp-ph","q-bio.GN"],"primary_cat":"cs.CV","authors_text":"Carl S. McTague, James P. Crutchfield","submitted_at":"2004-10-07T17:20:56Z","abstract_excerpt":"In the computational-mechanics structural analysis of one-dimensional cellular automata the following automata-theoretic analogue of the \\emph{change-point problem} from time series analysis arises: \\emph{Given a string $\\sigma$ and a collection $\\{\\mc{D}_i\\}$ of finite automata, identify the regions of $\\sigma$ that belong to each $\\mc{D}_i$ and, in particular, the boundaries separating them.} We present two methods for solving this \\emph{multi-regular language filtering problem}. The first, although providing the ideal solution, requires a stack, has a worst-case compute time that grows quad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"cs/0410017","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}