{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:Q7J42LJJLW2UAKG7ESNFSVDMIJ","short_pith_number":"pith:Q7J42LJJ","schema_version":"1.0","canonical_sha256":"87d3cd2d295db54028df249a59546c426cbb87df20bdd1d559eb138b5fc60571","source":{"kind":"arxiv","id":"1408.0532","version":1},"attestation_state":"computed","paper":{"title":"A unified framework for solving a general class of conditional and robust set-membership estimation problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Dario Piga, Diego Regruto, Jean-Bernard Lasserre, Vito Cerone","submitted_at":"2014-08-03T19:39:51Z","abstract_excerpt":"In this paper we present a unified framework for solving a general class of problems arising in the context of set-membership estimation/identification theory. More precisely, the paper aims at providing an original approach for the computation of optimal conditional and robust projection estimates in a nonlinear estimation setting where the operator relating the data and the parameter to be estimated is assumed to be a generic multivariate polynomial function and the uncertainties affecting the data are assumed to belong to semialgebraic sets. By noticing that the computation of both the cond"},"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":"1408.0532","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2014-08-03T19:39:51Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"a2c24242a78c9144953bcb43c78abc4389ffe51f6efa5f5cee23aaeadf4e830f","abstract_canon_sha256":"9f495a84bb14c10efdd26645ed3219151e3c9ec4af68b01d723641f59831010c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:57:51.602501Z","signature_b64":"oKY5L7FuD+DpMN6k9D3F3X8XlJCQo/24V/hdmQNKJu4P9LxVCIq2A4/LUZ6lZqBIcC5kLjHV0GFMLJ0YPzGoAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87d3cd2d295db54028df249a59546c426cbb87df20bdd1d559eb138b5fc60571","last_reissued_at":"2026-05-18T00:57:51.601870Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:57:51.601870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A unified framework for solving a general class of conditional and robust set-membership estimation problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Dario Piga, Diego Regruto, Jean-Bernard Lasserre, Vito Cerone","submitted_at":"2014-08-03T19:39:51Z","abstract_excerpt":"In this paper we present a unified framework for solving a general class of problems arising in the context of set-membership estimation/identification theory. More precisely, the paper aims at providing an original approach for the computation of optimal conditional and robust projection estimates in a nonlinear estimation setting where the operator relating the data and the parameter to be estimated is assumed to be a generic multivariate polynomial function and the uncertainties affecting the data are assumed to belong to semialgebraic sets. By noticing that the computation of both the cond"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1408.0532","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":"1408.0532","created_at":"2026-05-18T00:57:51.601965+00:00"},{"alias_kind":"arxiv_version","alias_value":"1408.0532v1","created_at":"2026-05-18T00:57:51.601965+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1408.0532","created_at":"2026-05-18T00:57:51.601965+00:00"},{"alias_kind":"pith_short_12","alias_value":"Q7J42LJJLW2U","created_at":"2026-05-18T12:28:43.426989+00:00"},{"alias_kind":"pith_short_16","alias_value":"Q7J42LJJLW2UAKG7","created_at":"2026-05-18T12:28:43.426989+00:00"},{"alias_kind":"pith_short_8","alias_value":"Q7J42LJJ","created_at":"2026-05-18T12:28:43.426989+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/Q7J42LJJLW2UAKG7ESNFSVDMIJ","json":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ.json","graph_json":"https://pith.science/api/pith-number/Q7J42LJJLW2UAKG7ESNFSVDMIJ/graph.json","events_json":"https://pith.science/api/pith-number/Q7J42LJJLW2UAKG7ESNFSVDMIJ/events.json","paper":"https://pith.science/paper/Q7J42LJJ"},"agent_actions":{"view_html":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ","download_json":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ.json","view_paper":"https://pith.science/paper/Q7J42LJJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1408.0532&json=true","fetch_graph":"https://pith.science/api/pith-number/Q7J42LJJLW2UAKG7ESNFSVDMIJ/graph.json","fetch_events":"https://pith.science/api/pith-number/Q7J42LJJLW2UAKG7ESNFSVDMIJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ/action/storage_attestation","attest_author":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ/action/author_attestation","sign_citation":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ/action/citation_signature","submit_replication":"https://pith.science/pith/Q7J42LJJLW2UAKG7ESNFSVDMIJ/action/replication_record"}},"created_at":"2026-05-18T00:57:51.601965+00:00","updated_at":"2026-05-18T00:57:51.601965+00:00"}