{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:OTJ2QUOA5VE5AK5OMGP4IGLJHM","short_pith_number":"pith:OTJ2QUOA","schema_version":"1.0","canonical_sha256":"74d3a851c0ed49d02bae619fc419693b29ba9c6fa81fc4d9d41267b436d1733f","source":{"kind":"arxiv","id":"1801.01959","version":1},"attestation_state":"computed","paper":{"title":"Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Ping-Tzan Huang, Tai-Lang Jong, Wen-Liang Hwang","submitted_at":"2018-01-06T03:31:20Z","abstract_excerpt":"Frames are the foundation of the linear operators used in the decomposition and reconstruction of signals, such as the discrete Fourier transform, Gabor, wavelets, and curvelet transforms. The emergence of sparse representation models has shifted of the emphasis in frame theory toward sparse l1-minimization problems. In this paper, we apply frame theory to the sparse representation of signals in which a synthesis dictionary is used for a frame and an analysis dictionary is used for a dual frame. We sought to formulate a novel dual frame design in which the sparse vector obtained through the de"},"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":"1801.01959","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-01-06T03:31:20Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ee3f945767b32bfb8c962e983a3a20f9f2151cdef01e70d9d5054d6da499e428","abstract_canon_sha256":"f2a695257255e1516e97f52dcda502c376d2c60ae9b7e8a98ce83cc9dcd75ca9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:30.942072Z","signature_b64":"oyk2NEPS12ta/32ko9vz136KOsMF8NhunYigEj5fm8VgwwVI2/MlWH6NhwiIA87GOR36tFhSP+kEmy3AUVX0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74d3a851c0ed49d02bae619fc419693b29ba9c6fa81fc4d9d41267b436d1733f","last_reissued_at":"2026-05-17T23:42:30.941623Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:30.941623Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Ping-Tzan Huang, Tai-Lang Jong, Wen-Liang Hwang","submitted_at":"2018-01-06T03:31:20Z","abstract_excerpt":"Frames are the foundation of the linear operators used in the decomposition and reconstruction of signals, such as the discrete Fourier transform, Gabor, wavelets, and curvelet transforms. The emergence of sparse representation models has shifted of the emphasis in frame theory toward sparse l1-minimization problems. In this paper, we apply frame theory to the sparse representation of signals in which a synthesis dictionary is used for a frame and an analysis dictionary is used for a dual frame. We sought to formulate a novel dual frame design in which the sparse vector obtained through the de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.01959","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":"1801.01959","created_at":"2026-05-17T23:42:30.941692+00:00"},{"alias_kind":"arxiv_version","alias_value":"1801.01959v1","created_at":"2026-05-17T23:42:30.941692+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.01959","created_at":"2026-05-17T23:42:30.941692+00:00"},{"alias_kind":"pith_short_12","alias_value":"OTJ2QUOA5VE5","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_16","alias_value":"OTJ2QUOA5VE5AK5O","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_8","alias_value":"OTJ2QUOA","created_at":"2026-05-18T12:32:43.782077+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/OTJ2QUOA5VE5AK5OMGP4IGLJHM","json":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM.json","graph_json":"https://pith.science/api/pith-number/OTJ2QUOA5VE5AK5OMGP4IGLJHM/graph.json","events_json":"https://pith.science/api/pith-number/OTJ2QUOA5VE5AK5OMGP4IGLJHM/events.json","paper":"https://pith.science/paper/OTJ2QUOA"},"agent_actions":{"view_html":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM","download_json":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM.json","view_paper":"https://pith.science/paper/OTJ2QUOA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1801.01959&json=true","fetch_graph":"https://pith.science/api/pith-number/OTJ2QUOA5VE5AK5OMGP4IGLJHM/graph.json","fetch_events":"https://pith.science/api/pith-number/OTJ2QUOA5VE5AK5OMGP4IGLJHM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM/action/storage_attestation","attest_author":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM/action/author_attestation","sign_citation":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM/action/citation_signature","submit_replication":"https://pith.science/pith/OTJ2QUOA5VE5AK5OMGP4IGLJHM/action/replication_record"}},"created_at":"2026-05-17T23:42:30.941692+00:00","updated_at":"2026-05-17T23:42:30.941692+00:00"}