{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:C2ETPVC67XTM5VIZVP7CRWEQNO","short_pith_number":"pith:C2ETPVC6","schema_version":"1.0","canonical_sha256":"168937d45efde6ced519abfe28d8906ba1242715fcc28153e6510d809e9b2719","source":{"kind":"arxiv","id":"1607.00127","version":2},"attestation_state":"computed","paper":{"title":"Tensor Network alternating linear scheme for MIMO Volterra system identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","cs.SY"],"primary_cat":"cs.NA","authors_text":"Kim Batselier, Ngai Wong, Zhongming Chen","submitted_at":"2016-07-01T07:01:01Z","abstract_excerpt":"This article introduces two Tensor Network-based iterative algorithms for the identification of high-order discrete-time nonlinear multiple-input multiple-output (MIMO) Volterra systems. The system identification problem is rewritten in terms of a Volterra tensor, which is never explicitly constructed, thus avoiding the curse of dimensionality. It is shown how each iteration of the two identification algorithms involves solving a linear system of low computational complexity. The proposed algorithms are guaranteed to monotonically converge and numerical stability is ensured through the use of "},"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":"1607.00127","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2016-07-01T07:01:01Z","cross_cats_sorted":["cs.CE","cs.SY"],"title_canon_sha256":"c6940a28081f651c69a7703db775e079e9f4178c490dcc4f927bfff1a3b5d2bd","abstract_canon_sha256":"c504b824cb2ec843f777ecbe7c5a567420909c2ff8ed52e7d260864361aacc81"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:02:04.044983Z","signature_b64":"eD6zx8i5xBoZFDVFc3hLKQf2JEEv81P14T0q6/FUjZg0+M2QefBGMbKxUKReOGJyiEN8W0F52Ggc6+qlOtHXCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"168937d45efde6ced519abfe28d8906ba1242715fcc28153e6510d809e9b2719","last_reissued_at":"2026-05-18T01:02:04.044280Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:02:04.044280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Tensor Network alternating linear scheme for MIMO Volterra system identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","cs.SY"],"primary_cat":"cs.NA","authors_text":"Kim Batselier, Ngai Wong, Zhongming Chen","submitted_at":"2016-07-01T07:01:01Z","abstract_excerpt":"This article introduces two Tensor Network-based iterative algorithms for the identification of high-order discrete-time nonlinear multiple-input multiple-output (MIMO) Volterra systems. The system identification problem is rewritten in terms of a Volterra tensor, which is never explicitly constructed, thus avoiding the curse of dimensionality. It is shown how each iteration of the two identification algorithms involves solving a linear system of low computational complexity. The proposed algorithms are guaranteed to monotonically converge and numerical stability is ensured through the use of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.00127","kind":"arxiv","version":2},"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":"1607.00127","created_at":"2026-05-18T01:02:04.044405+00:00"},{"alias_kind":"arxiv_version","alias_value":"1607.00127v2","created_at":"2026-05-18T01:02:04.044405+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.00127","created_at":"2026-05-18T01:02:04.044405+00:00"},{"alias_kind":"pith_short_12","alias_value":"C2ETPVC67XTM","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_16","alias_value":"C2ETPVC67XTM5VIZ","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_8","alias_value":"C2ETPVC6","created_at":"2026-05-18T12:30:09.641336+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/C2ETPVC67XTM5VIZVP7CRWEQNO","json":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO.json","graph_json":"https://pith.science/api/pith-number/C2ETPVC67XTM5VIZVP7CRWEQNO/graph.json","events_json":"https://pith.science/api/pith-number/C2ETPVC67XTM5VIZVP7CRWEQNO/events.json","paper":"https://pith.science/paper/C2ETPVC6"},"agent_actions":{"view_html":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO","download_json":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO.json","view_paper":"https://pith.science/paper/C2ETPVC6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1607.00127&json=true","fetch_graph":"https://pith.science/api/pith-number/C2ETPVC67XTM5VIZVP7CRWEQNO/graph.json","fetch_events":"https://pith.science/api/pith-number/C2ETPVC67XTM5VIZVP7CRWEQNO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO/action/storage_attestation","attest_author":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO/action/author_attestation","sign_citation":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO/action/citation_signature","submit_replication":"https://pith.science/pith/C2ETPVC67XTM5VIZVP7CRWEQNO/action/replication_record"}},"created_at":"2026-05-18T01:02:04.044405+00:00","updated_at":"2026-05-18T01:02:04.044405+00:00"}