{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:BDN6B3O2IZM3GRG725ESW73ECA","short_pith_number":"pith:BDN6B3O2","schema_version":"1.0","canonical_sha256":"08dbe0edda4659b344dfd7492b7f64103f77992df289b25577e9c370e5f9d47c","source":{"kind":"arxiv","id":"2306.10369","version":1},"attestation_state":"computed","paper":{"title":"Non-asymptotic System Identification for Linear Systems with Nonlinear Policies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY","stat.ML"],"primary_cat":"math.OC","authors_text":"Jeff Shamma, Na Li, Subhro Das, Tianpeng Zhang, Yingying Li","submitted_at":"2023-06-17T15:05:59Z","abstract_excerpt":"This paper considers a single-trajectory system identification problem for linear systems under general nonlinear and/or time-varying policies with i.i.d. random excitation noises. The problem is motivated by safe learning-based control for constrained linear systems, where the safe policies during the learning process are usually nonlinear and time-varying for satisfying the state and input constraints. In this paper, we provide a non-asymptotic error bound for least square estimation when the data trajectory is generated by any nonlinear and/or time-varying policies as long as the generated "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2306.10369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-06-17T15:05:59Z","cross_cats_sorted":["cs.SY","eess.SY","stat.ML"],"title_canon_sha256":"980186caa0bc14bcfa62d3fbaf8c0f98ac060440ad272cced4c3118a74ebb0fa","abstract_canon_sha256":"46d69014c52b989fd1dd56449122c0f13f8322d3f2ab632d99c7951eb7814957"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:21:36.991419Z","signature_b64":"khUfudMdNQzbE4mvhb+R1J96TGyQYY0DWVjEQlpJzj+qzH5ClcH4cYAX7W8SH2eiAAop3MRKQCQZ+s8KLwUnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08dbe0edda4659b344dfd7492b7f64103f77992df289b25577e9c370e5f9d47c","last_reissued_at":"2026-07-05T06:21:36.991062Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:21:36.991062Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Non-asymptotic System Identification for Linear Systems with Nonlinear Policies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY","stat.ML"],"primary_cat":"math.OC","authors_text":"Jeff Shamma, Na Li, Subhro Das, Tianpeng Zhang, Yingying Li","submitted_at":"2023-06-17T15:05:59Z","abstract_excerpt":"This paper considers a single-trajectory system identification problem for linear systems under general nonlinear and/or time-varying policies with i.i.d. random excitation noises. The problem is motivated by safe learning-based control for constrained linear systems, where the safe policies during the learning process are usually nonlinear and time-varying for satisfying the state and input constraints. In this paper, we provide a non-asymptotic error bound for least square estimation when the data trajectory is generated by any nonlinear and/or time-varying policies as long as the generated "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.10369","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2306.10369/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2306.10369","created_at":"2026-07-05T06:21:36.991124+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.10369v1","created_at":"2026-07-05T06:21:36.991124+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.10369","created_at":"2026-07-05T06:21:36.991124+00:00"},{"alias_kind":"pith_short_12","alias_value":"BDN6B3O2IZM3","created_at":"2026-07-05T06:21:36.991124+00:00"},{"alias_kind":"pith_short_16","alias_value":"BDN6B3O2IZM3GRG7","created_at":"2026-07-05T06:21:36.991124+00:00"},{"alias_kind":"pith_short_8","alias_value":"BDN6B3O2","created_at":"2026-07-05T06:21:36.991124+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.04157","citing_title":"Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems","ref_index":17,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA","json":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA.json","graph_json":"https://pith.science/api/pith-number/BDN6B3O2IZM3GRG725ESW73ECA/graph.json","events_json":"https://pith.science/api/pith-number/BDN6B3O2IZM3GRG725ESW73ECA/events.json","paper":"https://pith.science/paper/BDN6B3O2"},"agent_actions":{"view_html":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA","download_json":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA.json","view_paper":"https://pith.science/paper/BDN6B3O2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.10369&json=true","fetch_graph":"https://pith.science/api/pith-number/BDN6B3O2IZM3GRG725ESW73ECA/graph.json","fetch_events":"https://pith.science/api/pith-number/BDN6B3O2IZM3GRG725ESW73ECA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA/action/storage_attestation","attest_author":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA/action/author_attestation","sign_citation":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA/action/citation_signature","submit_replication":"https://pith.science/pith/BDN6B3O2IZM3GRG725ESW73ECA/action/replication_record"}},"created_at":"2026-07-05T06:21:36.991124+00:00","updated_at":"2026-07-05T06:21:36.991124+00:00"}