{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:23ILJVIHTYR22RLCW4ASTM3KWE","short_pith_number":"pith:23ILJVIH","schema_version":"1.0","canonical_sha256":"d6d0b4d5079e23ad4562b70129b36ab12bfff8cd62cb4dfb82f6f5cd0a3e546b","source":{"kind":"arxiv","id":"1708.03947","version":3},"attestation_state":"computed","paper":{"title":"Estimating Models with High-Order Noise Dynamics Using Semi-Parametric Weighted Null-Space Fitting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Cristian R. Rojas, Hakan Hjalmarsson, Miguel Galrinho","submitted_at":"2017-08-13T18:02:00Z","abstract_excerpt":"Standard system identification methods often provide inconsistent estimates with closed-loop data. With the prediction error method (PEM), this issue is solved by using a noise model that is flexible enough to capture the noise spectrum. However, a too flexible noise model (i.e., too many parameters) increases the model complexity, which can cause additional numerical problems for PEM. In this paper, we consider the weighted null-space fitting (WNSF) method. With this method, the system is first modeled using a non-parametric ARX model, which is then reduced to a parametric model of interest u"},"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":"1708.03947","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-08-13T18:02:00Z","cross_cats_sorted":[],"title_canon_sha256":"3565c2f5244fca88342e7121a61a72ab5009d2d072250225b70126501ebe9d04","abstract_canon_sha256":"b320ba0d93ccac6c51b80485c606a57f64488325cb77906bb20daf52eba751ea"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:25.502306Z","signature_b64":"qpyzF8+cnp8Ju8Inv027mtDnSiY8OPEDb8qOIF4pcDn0CeKAp3PbVCGdnqeFR+/alIaoHlK/0mgPtXfNy3S+CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6d0b4d5079e23ad4562b70129b36ab12bfff8cd62cb4dfb82f6f5cd0a3e546b","last_reissued_at":"2026-05-18T00:06:25.501629Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:25.501629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Estimating Models with High-Order Noise Dynamics Using Semi-Parametric Weighted Null-Space Fitting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Cristian R. Rojas, Hakan Hjalmarsson, Miguel Galrinho","submitted_at":"2017-08-13T18:02:00Z","abstract_excerpt":"Standard system identification methods often provide inconsistent estimates with closed-loop data. With the prediction error method (PEM), this issue is solved by using a noise model that is flexible enough to capture the noise spectrum. However, a too flexible noise model (i.e., too many parameters) increases the model complexity, which can cause additional numerical problems for PEM. In this paper, we consider the weighted null-space fitting (WNSF) method. With this method, the system is first modeled using a non-parametric ARX model, which is then reduced to a parametric model of interest u"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.03947","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1708.03947","created_at":"2026-05-18T00:06:25.501750+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.03947v3","created_at":"2026-05-18T00:06:25.501750+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.03947","created_at":"2026-05-18T00:06:25.501750+00:00"},{"alias_kind":"pith_short_12","alias_value":"23ILJVIHTYR2","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"23ILJVIHTYR22RLC","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"23ILJVIH","created_at":"2026-05-18T12:30:55.937587+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE","json":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE.json","graph_json":"https://pith.science/api/pith-number/23ILJVIHTYR22RLCW4ASTM3KWE/graph.json","events_json":"https://pith.science/api/pith-number/23ILJVIHTYR22RLCW4ASTM3KWE/events.json","paper":"https://pith.science/paper/23ILJVIH"},"agent_actions":{"view_html":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE","download_json":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE.json","view_paper":"https://pith.science/paper/23ILJVIH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.03947&json=true","fetch_graph":"https://pith.science/api/pith-number/23ILJVIHTYR22RLCW4ASTM3KWE/graph.json","fetch_events":"https://pith.science/api/pith-number/23ILJVIHTYR22RLCW4ASTM3KWE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE/action/storage_attestation","attest_author":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE/action/author_attestation","sign_citation":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE/action/citation_signature","submit_replication":"https://pith.science/pith/23ILJVIHTYR22RLCW4ASTM3KWE/action/replication_record"}},"created_at":"2026-05-18T00:06:25.501750+00:00","updated_at":"2026-05-18T00:06:25.501750+00:00"}