{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:3TQ5BQ2KJUWW6TRTHI5N3SB5VF","short_pith_number":"pith:3TQ5BQ2K","schema_version":"1.0","canonical_sha256":"dce1d0c34a4d2d6f4e333a3addc83da941f26c87d886177bed0e1758f295d339","source":{"kind":"arxiv","id":"1507.05365","version":1},"attestation_state":"computed","paper":{"title":"Structured Matching Pursuit for Reconstruction of Dynamic Sparse Channels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Fumiyuki Adachi, Guan Gui, Linglong Dai, Wei Dai, Xudong Zhu, Zhaocheng Wang","submitted_at":"2015-07-20T02:04:31Z","abstract_excerpt":"In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sp"},"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":"1507.05365","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2015-07-20T02:04:31Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"a3fbcd7c89b7d267e98ff7a17d5ec1175cfab6745b97e72ab42f758c891b4bf7","abstract_canon_sha256":"0db23b5f9a918a9fc850a9ba59636f75d178377a87ccfee0e33506a79cd9cbcd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:36:37.016789Z","signature_b64":"p17Ll3sMC6qGOGyuE/3QxLZ5dqnEaoK/cOUSJm0jrv1KOf8L98G1gxbZEKavkC0lqb/7q1CVjQ5mkUTR5movBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dce1d0c34a4d2d6f4e333a3addc83da941f26c87d886177bed0e1758f295d339","last_reissued_at":"2026-05-18T01:36:37.016159Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:36:37.016159Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structured Matching Pursuit for Reconstruction of Dynamic Sparse Channels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Fumiyuki Adachi, Guan Gui, Linglong Dai, Wei Dai, Xudong Zhu, Zhaocheng Wang","submitted_at":"2015-07-20T02:04:31Z","abstract_excerpt":"In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.05365","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":"1507.05365","created_at":"2026-05-18T01:36:37.016245+00:00"},{"alias_kind":"arxiv_version","alias_value":"1507.05365v1","created_at":"2026-05-18T01:36:37.016245+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.05365","created_at":"2026-05-18T01:36:37.016245+00:00"},{"alias_kind":"pith_short_12","alias_value":"3TQ5BQ2KJUWW","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_16","alias_value":"3TQ5BQ2KJUWW6TRT","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_8","alias_value":"3TQ5BQ2K","created_at":"2026-05-18T12:29:02.477457+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/3TQ5BQ2KJUWW6TRTHI5N3SB5VF","json":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF.json","graph_json":"https://pith.science/api/pith-number/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/graph.json","events_json":"https://pith.science/api/pith-number/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/events.json","paper":"https://pith.science/paper/3TQ5BQ2K"},"agent_actions":{"view_html":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF","download_json":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF.json","view_paper":"https://pith.science/paper/3TQ5BQ2K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1507.05365&json=true","fetch_graph":"https://pith.science/api/pith-number/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/graph.json","fetch_events":"https://pith.science/api/pith-number/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/action/storage_attestation","attest_author":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/action/author_attestation","sign_citation":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/action/citation_signature","submit_replication":"https://pith.science/pith/3TQ5BQ2KJUWW6TRTHI5N3SB5VF/action/replication_record"}},"created_at":"2026-05-18T01:36:37.016245+00:00","updated_at":"2026-05-18T01:36:37.016245+00:00"}