{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2010:IP3DREHKGI3R5KU5IDQ7Y743NP","short_pith_number":"pith:IP3DREHK","canonical_record":{"source":{"id":"1006.0054","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-06-01T04:54:20Z","cross_cats_sorted":["math.IT","math.NA","stat.AP"],"title_canon_sha256":"feaa66ba87f812c6dc91fcc6c24db1f13e8b91b55435b76b9a78817be955962e","abstract_canon_sha256":"a33422351d3a95835d49062ce027879378652146a2a7ec5ab55e3d85c760a525"},"schema_version":"1.0"},"canonical_sha256":"43f63890ea32371eaa9d40e1fc7f9b6bc384ad1b1cd43630891914ddc72156bc","source":{"kind":"arxiv","id":"1006.0054","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1006.0054","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"arxiv_version","alias_value":"1006.0054v3","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1006.0054","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"pith_short_12","alias_value":"IP3DREHKGI3R","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_16","alias_value":"IP3DREHKGI3R5KU5","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_8","alias_value":"IP3DREHK","created_at":"2026-05-18T12:26:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2010:IP3DREHKGI3R5KU5IDQ7Y743NP","target":"record","payload":{"canonical_record":{"source":{"id":"1006.0054","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-06-01T04:54:20Z","cross_cats_sorted":["math.IT","math.NA","stat.AP"],"title_canon_sha256":"feaa66ba87f812c6dc91fcc6c24db1f13e8b91b55435b76b9a78817be955962e","abstract_canon_sha256":"a33422351d3a95835d49062ce027879378652146a2a7ec5ab55e3d85c760a525"},"schema_version":"1.0"},"canonical_sha256":"43f63890ea32371eaa9d40e1fc7f9b6bc384ad1b1cd43630891914ddc72156bc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:19:43.734719Z","signature_b64":"BnnWM296JqPJPinB6vQDw0zYIKPiTiQv0rMKnzxgXyvN0eSevVMUX202t3rsWg07RuN2vn3wdYGjUYjgmJViCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43f63890ea32371eaa9d40e1fc7f9b6bc384ad1b1cd43630891914ddc72156bc","last_reissued_at":"2026-05-18T04:19:43.734143Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:19:43.734143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1006.0054","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:19:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QmDpe6nuhQCMUBfFGanm/qQwYhfI9At1a4wKrWHsKKnIF/nTH/uOoNuMEKq1E6JDSdWtZoaAEDhHA5F/J2DoCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T15:38:22.960631Z"},"content_sha256":"1ab4faaf7c80b6fa1d9bc42dc858ad62c538c9f05dab310e19de6f4e15e4a07d","schema_version":"1.0","event_id":"sha256:1ab4faaf7c80b6fa1d9bc42dc858ad62c538c9f05dab310e19de6f4e15e4a07d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2010:IP3DREHKGI3R5KU5IDQ7Y743NP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Anti-measurement Matrix Uncertainty Sparse Signal Recovery for Compressive Sensing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","math.NA","stat.AP"],"primary_cat":"cs.IT","authors_text":"Fei Wen, Jia Xu, Qun Wan, Yingning Peng, Yipeng Liu","submitted_at":"2010-06-01T04:54:20Z","abstract_excerpt":"Compressive sensing (CS) is a technique for estimating a sparse signal from the random measurements and the measurement matrix. Traditional sparse signal recovery methods have seriously degeneration with the measurement matrix uncertainty (MMU). Here the MMU is modeled as a bounded additive error. An anti-uncertainty constraint in the form of a mixed L2 and L1 norm is deduced from the sparse signal model with MMU. Then we combine the sparse constraint with the anti-uncertainty constraint to get an anti-uncertainty sparse signal recovery operator. Numerical simulations demonstrate that the prop"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1006.0054","kind":"arxiv","version":3},"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":"2026-05-18T04:19:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t6XnB9tV4yK5Xonj+EX4kL2YQLMhVNiRR5LQnFmNbApUxRqo/wSG4P7DAo3FCsFRPvchf1JYYQEH39hw8leBDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T15:38:22.960973Z"},"content_sha256":"0efba2bd357f39169ed6525e1bd80d9605929bd81df24047513c018736fa3f5e","schema_version":"1.0","event_id":"sha256:0efba2bd357f39169ed6525e1bd80d9605929bd81df24047513c018736fa3f5e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/bundle.json","state_url":"https://pith.science/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/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":"2026-06-27T15:38:22Z","links":{"resolver":"https://pith.science/pith/IP3DREHKGI3R5KU5IDQ7Y743NP","bundle":"https://pith.science/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/bundle.json","state":"https://pith.science/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IP3DREHKGI3R5KU5IDQ7Y743NP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2010:IP3DREHKGI3R5KU5IDQ7Y743NP","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":"a33422351d3a95835d49062ce027879378652146a2a7ec5ab55e3d85c760a525","cross_cats_sorted":["math.IT","math.NA","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-06-01T04:54:20Z","title_canon_sha256":"feaa66ba87f812c6dc91fcc6c24db1f13e8b91b55435b76b9a78817be955962e"},"schema_version":"1.0","source":{"id":"1006.0054","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1006.0054","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"arxiv_version","alias_value":"1006.0054v3","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1006.0054","created_at":"2026-05-18T04:19:43Z"},{"alias_kind":"pith_short_12","alias_value":"IP3DREHKGI3R","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_16","alias_value":"IP3DREHKGI3R5KU5","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_8","alias_value":"IP3DREHK","created_at":"2026-05-18T12:26:09Z"}],"graph_snapshots":[{"event_id":"sha256:0efba2bd357f39169ed6525e1bd80d9605929bd81df24047513c018736fa3f5e","target":"graph","created_at":"2026-05-18T04:19:43Z","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":"Compressive sensing (CS) is a technique for estimating a sparse signal from the random measurements and the measurement matrix. Traditional sparse signal recovery methods have seriously degeneration with the measurement matrix uncertainty (MMU). Here the MMU is modeled as a bounded additive error. An anti-uncertainty constraint in the form of a mixed L2 and L1 norm is deduced from the sparse signal model with MMU. Then we combine the sparse constraint with the anti-uncertainty constraint to get an anti-uncertainty sparse signal recovery operator. Numerical simulations demonstrate that the prop","authors_text":"Fei Wen, Jia Xu, Qun Wan, Yingning Peng, Yipeng Liu","cross_cats":["math.IT","math.NA","stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-06-01T04:54:20Z","title":"Anti-measurement Matrix Uncertainty Sparse Signal Recovery for Compressive Sensing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1006.0054","kind":"arxiv","version":3},"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":"sha256:1ab4faaf7c80b6fa1d9bc42dc858ad62c538c9f05dab310e19de6f4e15e4a07d","target":"record","created_at":"2026-05-18T04:19:43Z","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":"a33422351d3a95835d49062ce027879378652146a2a7ec5ab55e3d85c760a525","cross_cats_sorted":["math.IT","math.NA","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-06-01T04:54:20Z","title_canon_sha256":"feaa66ba87f812c6dc91fcc6c24db1f13e8b91b55435b76b9a78817be955962e"},"schema_version":"1.0","source":{"id":"1006.0054","kind":"arxiv","version":3}},"canonical_sha256":"43f63890ea32371eaa9d40e1fc7f9b6bc384ad1b1cd43630891914ddc72156bc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"43f63890ea32371eaa9d40e1fc7f9b6bc384ad1b1cd43630891914ddc72156bc","first_computed_at":"2026-05-18T04:19:43.734143Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:19:43.734143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BnnWM296JqPJPinB6vQDw0zYIKPiTiQv0rMKnzxgXyvN0eSevVMUX202t3rsWg07RuN2vn3wdYGjUYjgmJViCw==","signature_status":"signed_v1","signed_at":"2026-05-18T04:19:43.734719Z","signed_message":"canonical_sha256_bytes"},"source_id":"1006.0054","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ab4faaf7c80b6fa1d9bc42dc858ad62c538c9f05dab310e19de6f4e15e4a07d","sha256:0efba2bd357f39169ed6525e1bd80d9605929bd81df24047513c018736fa3f5e"],"state_sha256":"d5d86e28cc9bff94595501079b15eb4b2acf377c4292f7c4354243a6b31038ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SNdsmXMW8mVkM8+NHCuC+LuCmBSqnEZ4hzixb84KduMMNupMmc/UucsESP9075JWdZPb9Ep++ITVS4vHrkXqAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T15:38:22.962889Z","bundle_sha256":"9bc8ff439d03f2981fcd18520bb1e75d6832567e8c78e66e797e67e4c5445013"}}