{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:NXICJ3RJXIVYG4LQXROZ3CKBTB","short_pith_number":"pith:NXICJ3RJ","schema_version":"1.0","canonical_sha256":"6dd024ee29ba2b837170bc5d9d894198778090d29ade303fe34488fed98f4f44","source":{"kind":"arxiv","id":"1603.09022","version":1},"attestation_state":"computed","paper":{"title":"Variable p norm constrained LMS algorithm based on gradient of root relative deviation.pdf","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Fei Chen, Jiasong Wu, Yong Feng","submitted_at":"2016-03-30T02:22:59Z","abstract_excerpt":"A new Lp-norm constraint least mean square (Lp-LMS) algorithm with new strategy of varying p is presented, which is applied to system identification in this letter. The parameter p is iteratively adjusted by the gradient method applied to the root relative deviation of the estimated weight vector. Numerical simulations show that this new algorithm achieves lower steady-state error as well as equally fast convergence compared with the traditional Lp-LMS and LMS algorithms in the application setting of sparse system identification in the presence of noise."},"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":"1603.09022","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2016-03-30T02:22:59Z","cross_cats_sorted":[],"title_canon_sha256":"68b78cdd4d7c0da2e21cc865b906bec88d60b8d9883a03293838d425a21c74d7","abstract_canon_sha256":"2c3d9f7015f0ce64ef4027e963093bc9213a7396e5052c19b0e51313116c5d95"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:03.978772Z","signature_b64":"vamNSS0Fai8q6i1q0KP++iE0Oz54gQiLa5Rux4YJcGlWx1yvnV7bbbqlDirant/nLWMwpG4gJP/n0u/XUYBgAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6dd024ee29ba2b837170bc5d9d894198778090d29ade303fe34488fed98f4f44","last_reissued_at":"2026-05-18T01:18:03.978058Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:03.978058Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Variable p norm constrained LMS algorithm based on gradient of root relative deviation.pdf","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Fei Chen, Jiasong Wu, Yong Feng","submitted_at":"2016-03-30T02:22:59Z","abstract_excerpt":"A new Lp-norm constraint least mean square (Lp-LMS) algorithm with new strategy of varying p is presented, which is applied to system identification in this letter. The parameter p is iteratively adjusted by the gradient method applied to the root relative deviation of the estimated weight vector. Numerical simulations show that this new algorithm achieves lower steady-state error as well as equally fast convergence compared with the traditional Lp-LMS and LMS algorithms in the application setting of sparse system identification in the presence of noise."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.09022","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":"1603.09022","created_at":"2026-05-18T01:18:03.978154+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.09022v1","created_at":"2026-05-18T01:18:03.978154+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.09022","created_at":"2026-05-18T01:18:03.978154+00:00"},{"alias_kind":"pith_short_12","alias_value":"NXICJ3RJXIVY","created_at":"2026-05-18T12:30:36.002864+00:00"},{"alias_kind":"pith_short_16","alias_value":"NXICJ3RJXIVYG4LQ","created_at":"2026-05-18T12:30:36.002864+00:00"},{"alias_kind":"pith_short_8","alias_value":"NXICJ3RJ","created_at":"2026-05-18T12:30:36.002864+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/NXICJ3RJXIVYG4LQXROZ3CKBTB","json":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB.json","graph_json":"https://pith.science/api/pith-number/NXICJ3RJXIVYG4LQXROZ3CKBTB/graph.json","events_json":"https://pith.science/api/pith-number/NXICJ3RJXIVYG4LQXROZ3CKBTB/events.json","paper":"https://pith.science/paper/NXICJ3RJ"},"agent_actions":{"view_html":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB","download_json":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB.json","view_paper":"https://pith.science/paper/NXICJ3RJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.09022&json=true","fetch_graph":"https://pith.science/api/pith-number/NXICJ3RJXIVYG4LQXROZ3CKBTB/graph.json","fetch_events":"https://pith.science/api/pith-number/NXICJ3RJXIVYG4LQXROZ3CKBTB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB/action/storage_attestation","attest_author":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB/action/author_attestation","sign_citation":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB/action/citation_signature","submit_replication":"https://pith.science/pith/NXICJ3RJXIVYG4LQXROZ3CKBTB/action/replication_record"}},"created_at":"2026-05-18T01:18:03.978154+00:00","updated_at":"2026-05-18T01:18:03.978154+00:00"}