{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:46Z4QLUHCFLWJMQBV6IQRA724Z","short_pith_number":"pith:46Z4QLUH","schema_version":"1.0","canonical_sha256":"e7b3c82e87115764b201af910883fae65c162a788435be1c16382f7b7a813957","source":{"kind":"arxiv","id":"1705.09446","version":1},"attestation_state":"computed","paper":{"title":"Joint Sparse Recovery With Semisupervised MUSIC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Biao Hou, Licheng Jiao, Zaidao Wen","submitted_at":"2017-05-26T06:37:47Z","abstract_excerpt":"Discrete multiple signal classification (MUSIC) with its low computational cost and mild condition requirement becomes a significant noniterative algorithm for joint sparse recovery (JSR). However, it fails in rank defective problem caused by coherent or limited amount of multiple measurement vectors (MMVs). In this letter, we provide a novel sight to address this problem by interpreting JSR as a binary classification problem with respect to atoms. Meanwhile, MUSIC essentially constructs a supervised classifier based on the labeled MMVs so that its performance will heavily depend on the qualit"},"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":"1705.09446","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-05-26T06:37:47Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"12fb0ab17ea776c57fe6e976036f609193c3e976f2898f8f0c8ce1c66f428a45","abstract_canon_sha256":"fc38d08efb32da5e3ee79c891fdd57db95f5d28c52aa38c4d99699798fc4a6c1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:38.689154Z","signature_b64":"CAF5xJJu7mi0dikZ9dSWq78svN9TqRjmp6AoORgV7cKPgbBOretLt7Lqv0se26Nt2ZxJ/im4XK8V0y2aO+M8BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e7b3c82e87115764b201af910883fae65c162a788435be1c16382f7b7a813957","last_reissued_at":"2026-05-18T00:43:38.688591Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:38.688591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Joint Sparse Recovery With Semisupervised MUSIC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Biao Hou, Licheng Jiao, Zaidao Wen","submitted_at":"2017-05-26T06:37:47Z","abstract_excerpt":"Discrete multiple signal classification (MUSIC) with its low computational cost and mild condition requirement becomes a significant noniterative algorithm for joint sparse recovery (JSR). However, it fails in rank defective problem caused by coherent or limited amount of multiple measurement vectors (MMVs). In this letter, we provide a novel sight to address this problem by interpreting JSR as a binary classification problem with respect to atoms. Meanwhile, MUSIC essentially constructs a supervised classifier based on the labeled MMVs so that its performance will heavily depend on the qualit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.09446","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":"1705.09446","created_at":"2026-05-18T00:43:38.688659+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.09446v1","created_at":"2026-05-18T00:43:38.688659+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.09446","created_at":"2026-05-18T00:43:38.688659+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/46Z4QLUHCFLWJMQBV6IQRA724Z","json":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z.json","graph_json":"https://pith.science/api/pith-number/46Z4QLUHCFLWJMQBV6IQRA724Z/graph.json","events_json":"https://pith.science/api/pith-number/46Z4QLUHCFLWJMQBV6IQRA724Z/events.json","paper":"https://pith.science/paper/46Z4QLUH"},"agent_actions":{"view_html":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z","download_json":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z.json","view_paper":"https://pith.science/paper/46Z4QLUH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.09446&json=true","fetch_graph":"https://pith.science/api/pith-number/46Z4QLUHCFLWJMQBV6IQRA724Z/graph.json","fetch_events":"https://pith.science/api/pith-number/46Z4QLUHCFLWJMQBV6IQRA724Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z/action/storage_attestation","attest_author":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z/action/author_attestation","sign_citation":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z/action/citation_signature","submit_replication":"https://pith.science/pith/46Z4QLUHCFLWJMQBV6IQRA724Z/action/replication_record"}},"created_at":"2026-05-18T00:43:38.688659+00:00","updated_at":"2026-05-18T00:43:38.688659+00:00"}