{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2WYOLDZ7QJIP24KALOPLCXTSDF","short_pith_number":"pith:2WYOLDZ7","schema_version":"1.0","canonical_sha256":"d5b0e58f3f8250fd71405b9eb15e721952d0f1d8c0688caf17e4c32a028fa203","source":{"kind":"arxiv","id":"1705.00178","version":1},"attestation_state":"computed","paper":{"title":"Parameter reduction in nonlinear state-space identification of hysteresis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Aerospace, Alireza Fakhrizadeh Esfahani (Vrije Universiteit Brussel, ELEC Department, ELEC Department), Jean-Philippe No\\\"el (Vrije Universiteit Brussel, Johan Schoukens (Vrije Universiteit Brussel, Koen Tiels (Vrije Universiteit Brussel, Mechanical Engineering Department), Philippe Dreesen (Vrije Universiteit Brussel, Space Structures, Systems Laboratory, University of Li\\`ege","submitted_at":"2017-04-29T12:21:52Z","abstract_excerpt":"Hysteresis is a highly nonlinear phenomenon, showing up in a wide variety of science and engineering problems. The identification of hysteretic systems from input-output data is a challenging task. Recent work on black-box polynomial nonlinear state-space modeling for hysteresis identification has provided promising results, but struggles with a large number of parameters due to the use of multivariate polynomials. This drawback is tackled in the current paper by applying a decoupling approach that results in a more parsimonious representation involving univariate polynomials. This work is car"},"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":"1705.00178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-04-29T12:21:52Z","cross_cats_sorted":[],"title_canon_sha256":"cdd1e1139ec680e9b82b9d19e288a564ebfa90675eddb475757082aaffbae5d7","abstract_canon_sha256":"201346084616a4b62ad5bdeffa23d8271b3b93177d788637fc853ebd7746dbc2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:14.027592Z","signature_b64":"m15Gp2cVfIsJD9Y3OfBF1/ZM31njH9KNzp9NlvTpyaPauJ/fg1EJpDaq3dAu+c82K6AWe5hU1a5IXqaLwSRJAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5b0e58f3f8250fd71405b9eb15e721952d0f1d8c0688caf17e4c32a028fa203","last_reissued_at":"2026-05-18T00:21:14.027223Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:14.027223Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parameter reduction in nonlinear state-space identification of hysteresis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Aerospace, Alireza Fakhrizadeh Esfahani (Vrije Universiteit Brussel, ELEC Department, ELEC Department), Jean-Philippe No\\\"el (Vrije Universiteit Brussel, Johan Schoukens (Vrije Universiteit Brussel, Koen Tiels (Vrije Universiteit Brussel, Mechanical Engineering Department), Philippe Dreesen (Vrije Universiteit Brussel, Space Structures, Systems Laboratory, University of Li\\`ege","submitted_at":"2017-04-29T12:21:52Z","abstract_excerpt":"Hysteresis is a highly nonlinear phenomenon, showing up in a wide variety of science and engineering problems. The identification of hysteretic systems from input-output data is a challenging task. Recent work on black-box polynomial nonlinear state-space modeling for hysteresis identification has provided promising results, but struggles with a large number of parameters due to the use of multivariate polynomials. This drawback is tackled in the current paper by applying a decoupling approach that results in a more parsimonious representation involving univariate polynomials. This work is car"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.00178","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":"1705.00178","created_at":"2026-05-18T00:21:14.027277+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.00178v1","created_at":"2026-05-18T00:21:14.027277+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.00178","created_at":"2026-05-18T00:21:14.027277+00:00"},{"alias_kind":"pith_short_12","alias_value":"2WYOLDZ7QJIP","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2WYOLDZ7QJIP24KA","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2WYOLDZ7","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/2WYOLDZ7QJIP24KALOPLCXTSDF","json":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF.json","graph_json":"https://pith.science/api/pith-number/2WYOLDZ7QJIP24KALOPLCXTSDF/graph.json","events_json":"https://pith.science/api/pith-number/2WYOLDZ7QJIP24KALOPLCXTSDF/events.json","paper":"https://pith.science/paper/2WYOLDZ7"},"agent_actions":{"view_html":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF","download_json":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF.json","view_paper":"https://pith.science/paper/2WYOLDZ7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.00178&json=true","fetch_graph":"https://pith.science/api/pith-number/2WYOLDZ7QJIP24KALOPLCXTSDF/graph.json","fetch_events":"https://pith.science/api/pith-number/2WYOLDZ7QJIP24KALOPLCXTSDF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF/action/storage_attestation","attest_author":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF/action/author_attestation","sign_citation":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF/action/citation_signature","submit_replication":"https://pith.science/pith/2WYOLDZ7QJIP24KALOPLCXTSDF/action/replication_record"}},"created_at":"2026-05-18T00:21:14.027277+00:00","updated_at":"2026-05-18T00:21:14.027277+00:00"}