{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:ELB3QWPNCTPDWHCHS66VHYIG4L","short_pith_number":"pith:ELB3QWPN","schema_version":"1.0","canonical_sha256":"22c3b859ed14de3b1c4797bd53e106e2fb2dd76625b1ed4915bc57c82fe7a841","source":{"kind":"arxiv","id":"1503.07338","version":1},"attestation_state":"computed","paper":{"title":"A New Recursive Least-Squares Method with Multiple Forgetting Schemes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Andrea Peruffo, Francesco Fraccaroli, Mattia Zorzi","submitted_at":"2015-03-25T11:23:58Z","abstract_excerpt":"We propose a recursive least-squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least-squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method."},"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":"1503.07338","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2015-03-25T11:23:58Z","cross_cats_sorted":[],"title_canon_sha256":"68c74b39fda2bd6fe03eddc609b1255b1670c845894dc8a8973e44256e83280d","abstract_canon_sha256":"0d9d1e34a4104e462865623b81136bfdb54872beb4d43769093f56eb2afaaa3b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:20:21.358457Z","signature_b64":"43MVHCI/qg/lrK8nqucvQ7D1WbRK4gkQF9RQX+cYo76BqL3/i/Yareo23C8XtFRoY4puyni6wgIMQPxWZObSCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22c3b859ed14de3b1c4797bd53e106e2fb2dd76625b1ed4915bc57c82fe7a841","last_reissued_at":"2026-05-18T02:20:21.357799Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:20:21.357799Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A New Recursive Least-Squares Method with Multiple Forgetting Schemes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Andrea Peruffo, Francesco Fraccaroli, Mattia Zorzi","submitted_at":"2015-03-25T11:23:58Z","abstract_excerpt":"We propose a recursive least-squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least-squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.07338","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1503.07338","created_at":"2026-05-18T02:20:21.357891+00:00"},{"alias_kind":"arxiv_version","alias_value":"1503.07338v1","created_at":"2026-05-18T02:20:21.357891+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.07338","created_at":"2026-05-18T02:20:21.357891+00:00"},{"alias_kind":"pith_short_12","alias_value":"ELB3QWPNCTPD","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_16","alias_value":"ELB3QWPNCTPDWHCH","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_8","alias_value":"ELB3QWPN","created_at":"2026-05-18T12:29:19.899920+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/ELB3QWPNCTPDWHCHS66VHYIG4L","json":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L.json","graph_json":"https://pith.science/api/pith-number/ELB3QWPNCTPDWHCHS66VHYIG4L/graph.json","events_json":"https://pith.science/api/pith-number/ELB3QWPNCTPDWHCHS66VHYIG4L/events.json","paper":"https://pith.science/paper/ELB3QWPN"},"agent_actions":{"view_html":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L","download_json":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L.json","view_paper":"https://pith.science/paper/ELB3QWPN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1503.07338&json=true","fetch_graph":"https://pith.science/api/pith-number/ELB3QWPNCTPDWHCHS66VHYIG4L/graph.json","fetch_events":"https://pith.science/api/pith-number/ELB3QWPNCTPDWHCHS66VHYIG4L/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L/action/storage_attestation","attest_author":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L/action/author_attestation","sign_citation":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L/action/citation_signature","submit_replication":"https://pith.science/pith/ELB3QWPNCTPDWHCHS66VHYIG4L/action/replication_record"}},"created_at":"2026-05-18T02:20:21.357891+00:00","updated_at":"2026-05-18T02:20:21.357891+00:00"}