{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:TGSXQVPN55YQP2IMUTELMUUKF7","short_pith_number":"pith:TGSXQVPN","canonical_record":{"source":{"id":"1108.5037","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-08-25T08:35:39Z","cross_cats_sorted":["cs.SY","math.IT","math.OC"],"title_canon_sha256":"9c031a278c0f591b04fdc5c1cb96a0fca61e76707a53915bc760fb840d52458a","abstract_canon_sha256":"63e78ff00fa431ef1d4b1b1ba1e18eb58d9114a79cc1d7fee3d1ec77207b88ca"},"schema_version":"1.0"},"canonical_sha256":"99a57855edef7107e90ca4c8b6528a2fdc6cab38520dd15631458c7c21f106ce","source":{"kind":"arxiv","id":"1108.5037","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.5037","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"arxiv_version","alias_value":"1108.5037v2","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.5037","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"pith_short_12","alias_value":"TGSXQVPN55YQ","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"TGSXQVPN55YQP2IM","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"TGSXQVPN","created_at":"2026-05-18T12:26:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:TGSXQVPN55YQP2IMUTELMUUKF7","target":"record","payload":{"canonical_record":{"source":{"id":"1108.5037","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-08-25T08:35:39Z","cross_cats_sorted":["cs.SY","math.IT","math.OC"],"title_canon_sha256":"9c031a278c0f591b04fdc5c1cb96a0fca61e76707a53915bc760fb840d52458a","abstract_canon_sha256":"63e78ff00fa431ef1d4b1b1ba1e18eb58d9114a79cc1d7fee3d1ec77207b88ca"},"schema_version":"1.0"},"canonical_sha256":"99a57855edef7107e90ca4c8b6528a2fdc6cab38520dd15631458c7c21f106ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:00:48.278200Z","signature_b64":"LWYmg70eE0Jp3pEPIUMWvI+T4tZE3xA79xbKClUqTia7OaVZ3bgKEn3UTYSuvsj7OKv+UtSZc/U+EVr4j7WEDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99a57855edef7107e90ca4c8b6528a2fdc6cab38520dd15631458c7c21f106ce","last_reissued_at":"2026-05-18T02:00:48.277485Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:00:48.277485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1108.5037","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:00:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E8NIDKoJMzwsiYpz6Tn9LVpw5lsuT+Z+XJ1MYhO7INTvrfyVFWZ7Wbq217HRUZCX8cHAKVDGbcdIlkGktvVlCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T00:14:49.008838Z"},"content_sha256":"4f6c8c759fdc3c8458edd9ee8f04458ced1ea38ec69900194d4cfa3450954ee6","schema_version":"1.0","event_id":"sha256:4f6c8c759fdc3c8458edd9ee8f04458ced1ea38ec69900194d4cfa3450954ee6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:TGSXQVPN55YQP2IMUTELMUUKF7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Orthonormal Expansion l1-Minimization Algorithms for Compressed Sensing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.IT","math.OC"],"primary_cat":"cs.IT","authors_text":"Cishen Zhang, Jun Deng, Wenmiao Lu, Zai Yang","submitted_at":"2011-08-25T08:35:39Z","abstract_excerpt":"Compressed sensing aims at reconstructing sparse signals from significantly reduced number of samples, and a popular reconstruction approach is $\\ell_1$-norm minimization. In this correspondence, a method called orthonormal expansion is presented to reformulate the basis pursuit problem for noiseless compressed sensing. Two algorithms are proposed based on convex optimization: one exactly solves the problem and the other is a relaxed version of the first one. The latter can be considered as a modified iterative soft thresholding algorithm and is easy to implement. Numerical simulation shows th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.5037","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:00:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xheg2NzkyE+fODz+yQYog0/FgR4R5AYb9brbpsM3Wl4V2okMqqfOvdqnynAO+7rdWObyViakDdJZWRzcWeouBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T00:14:49.009190Z"},"content_sha256":"d196f7cf04c24bad75315763836cd69b4330b98bce98c4716c8a3e3b7fa97013","schema_version":"1.0","event_id":"sha256:d196f7cf04c24bad75315763836cd69b4330b98bce98c4716c8a3e3b7fa97013"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TGSXQVPN55YQP2IMUTELMUUKF7/bundle.json","state_url":"https://pith.science/pith/TGSXQVPN55YQP2IMUTELMUUKF7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TGSXQVPN55YQP2IMUTELMUUKF7/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-23T00:14:49Z","links":{"resolver":"https://pith.science/pith/TGSXQVPN55YQP2IMUTELMUUKF7","bundle":"https://pith.science/pith/TGSXQVPN55YQP2IMUTELMUUKF7/bundle.json","state":"https://pith.science/pith/TGSXQVPN55YQP2IMUTELMUUKF7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TGSXQVPN55YQP2IMUTELMUUKF7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:TGSXQVPN55YQP2IMUTELMUUKF7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"63e78ff00fa431ef1d4b1b1ba1e18eb58d9114a79cc1d7fee3d1ec77207b88ca","cross_cats_sorted":["cs.SY","math.IT","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-08-25T08:35:39Z","title_canon_sha256":"9c031a278c0f591b04fdc5c1cb96a0fca61e76707a53915bc760fb840d52458a"},"schema_version":"1.0","source":{"id":"1108.5037","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.5037","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"arxiv_version","alias_value":"1108.5037v2","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.5037","created_at":"2026-05-18T02:00:48Z"},{"alias_kind":"pith_short_12","alias_value":"TGSXQVPN55YQ","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"TGSXQVPN55YQP2IM","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"TGSXQVPN","created_at":"2026-05-18T12:26:42Z"}],"graph_snapshots":[{"event_id":"sha256:d196f7cf04c24bad75315763836cd69b4330b98bce98c4716c8a3e3b7fa97013","target":"graph","created_at":"2026-05-18T02:00:48Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Compressed sensing aims at reconstructing sparse signals from significantly reduced number of samples, and a popular reconstruction approach is $\\ell_1$-norm minimization. In this correspondence, a method called orthonormal expansion is presented to reformulate the basis pursuit problem for noiseless compressed sensing. Two algorithms are proposed based on convex optimization: one exactly solves the problem and the other is a relaxed version of the first one. The latter can be considered as a modified iterative soft thresholding algorithm and is easy to implement. Numerical simulation shows th","authors_text":"Cishen Zhang, Jun Deng, Wenmiao Lu, Zai Yang","cross_cats":["cs.SY","math.IT","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-08-25T08:35:39Z","title":"Orthonormal Expansion l1-Minimization Algorithms for Compressed Sensing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.5037","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4f6c8c759fdc3c8458edd9ee8f04458ced1ea38ec69900194d4cfa3450954ee6","target":"record","created_at":"2026-05-18T02:00:48Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"63e78ff00fa431ef1d4b1b1ba1e18eb58d9114a79cc1d7fee3d1ec77207b88ca","cross_cats_sorted":["cs.SY","math.IT","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-08-25T08:35:39Z","title_canon_sha256":"9c031a278c0f591b04fdc5c1cb96a0fca61e76707a53915bc760fb840d52458a"},"schema_version":"1.0","source":{"id":"1108.5037","kind":"arxiv","version":2}},"canonical_sha256":"99a57855edef7107e90ca4c8b6528a2fdc6cab38520dd15631458c7c21f106ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99a57855edef7107e90ca4c8b6528a2fdc6cab38520dd15631458c7c21f106ce","first_computed_at":"2026-05-18T02:00:48.277485Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:00:48.277485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LWYmg70eE0Jp3pEPIUMWvI+T4tZE3xA79xbKClUqTia7OaVZ3bgKEn3UTYSuvsj7OKv+UtSZc/U+EVr4j7WEDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:00:48.278200Z","signed_message":"canonical_sha256_bytes"},"source_id":"1108.5037","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4f6c8c759fdc3c8458edd9ee8f04458ced1ea38ec69900194d4cfa3450954ee6","sha256:d196f7cf04c24bad75315763836cd69b4330b98bce98c4716c8a3e3b7fa97013"],"state_sha256":"a3fbafe532d788cf27d5b6dbb2db7cf791a218c9b949f736093a9f4ee714c605"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"13gUCUqPShChQhNQI4YuNTbg6SHptcViU7au/2CTTD/y9HUx2uiuhbGNDpEyh3pTXEH0kqxHquyL0j3jj3q4Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T00:14:49.011369Z","bundle_sha256":"b526bc0e4bc0d14bae8fc911363789b041dc6c99423146f990fc5dacb606200d"}}