{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:WPLKSI4UTADSKFJ5ICCJTKCZ5N","short_pith_number":"pith:WPLKSI4U","canonical_record":{"source":{"id":"1110.3774","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-10-17T19:29:39Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"166f7d894459c126182de9ca1a4c6d83afa7aee01e406c0b29fd718fb56e592e","abstract_canon_sha256":"3ecf93c46ca9ca4796ba052024e7141c50c1bca93b644a407bfedf0f5c57ac48"},"schema_version":"1.0"},"canonical_sha256":"b3d6a92394980725153d408499a859eb7ad11da963e281490893a334132f4492","source":{"kind":"arxiv","id":"1110.3774","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1110.3774","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"arxiv_version","alias_value":"1110.3774v1","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.3774","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"pith_short_12","alias_value":"WPLKSI4UTADS","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"WPLKSI4UTADSKFJ5","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"WPLKSI4U","created_at":"2026-05-18T12:26:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:WPLKSI4UTADSKFJ5ICCJTKCZ5N","target":"record","payload":{"canonical_record":{"source":{"id":"1110.3774","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-10-17T19:29:39Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"166f7d894459c126182de9ca1a4c6d83afa7aee01e406c0b29fd718fb56e592e","abstract_canon_sha256":"3ecf93c46ca9ca4796ba052024e7141c50c1bca93b644a407bfedf0f5c57ac48"},"schema_version":"1.0"},"canonical_sha256":"b3d6a92394980725153d408499a859eb7ad11da963e281490893a334132f4492","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:20:48.096609Z","signature_b64":"QhHQFEeYOhJVVtw4LCYHvMyo7xzdm/k6R3rZ5VLvWK4NQdePD7vl378Dgq5/kpslll92f7dmMr3wF8b9Cm/rBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3d6a92394980725153d408499a859eb7ad11da963e281490893a334132f4492","last_reissued_at":"2026-05-18T02:20:48.095890Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:20:48.095890Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1110.3774","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:20:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rl9spE03aqwcH2G2OPU3WMiqGU+1n90enhBVqV6+x/xAdO2/UgDhRtpuT4p4Rh1O7YJlBR6DwXsJVpAHIM5oDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T00:42:24.789649Z"},"content_sha256":"7d6ee5cc5e76716655a53dd24dcce7a8fc298c39baea9def2fdc474e34321be6","schema_version":"1.0","event_id":"sha256:7d6ee5cc5e76716655a53dd24dcce7a8fc298c39baea9def2fdc474e34321be6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:WPLKSI4UTADSKFJ5ICCJTKCZ5N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Time-Stampless Adaptive Nonuniform Sampling for Stochastic Signals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Muriel Medard, Soheil Feizi, Vivek K Goyal","submitted_at":"2011-10-17T19:29:39Z","abstract_excerpt":"In this paper, we introduce a time-stampless adaptive nonuniform sampling (TANS) framework, in which time increments between samples are determined by a function of the $m$ most recent increments and sample values. Since only past samples are used in computing time increments, it is not necessary to save sampling times (time stamps) for use in the reconstruction process. We focus on two TANS schemes for discrete-time stochastic signals: a greedy method, and a method based on dynamic programming. We analyze the performances of these schemes by computing (or bounding) their trade-offs between sa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.3774","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:20:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GBVdAJN5u8y47IM/TsJE0Ln9t8AdnvehqDyufEgXSHLho6n4ERzh4g3ky/jtMjrgWKfs5GM4+q3IH0ys73MfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T00:42:24.790359Z"},"content_sha256":"64e07359c4f6074e895620824ba40c3f9070f246504d71a19ef76d262217fd95","schema_version":"1.0","event_id":"sha256:64e07359c4f6074e895620824ba40c3f9070f246504d71a19ef76d262217fd95"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/bundle.json","state_url":"https://pith.science/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/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":"2026-05-25T00:42:24Z","links":{"resolver":"https://pith.science/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N","bundle":"https://pith.science/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/bundle.json","state":"https://pith.science/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WPLKSI4UTADSKFJ5ICCJTKCZ5N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:WPLKSI4UTADSKFJ5ICCJTKCZ5N","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":"3ecf93c46ca9ca4796ba052024e7141c50c1bca93b644a407bfedf0f5c57ac48","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-10-17T19:29:39Z","title_canon_sha256":"166f7d894459c126182de9ca1a4c6d83afa7aee01e406c0b29fd718fb56e592e"},"schema_version":"1.0","source":{"id":"1110.3774","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1110.3774","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"arxiv_version","alias_value":"1110.3774v1","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.3774","created_at":"2026-05-18T02:20:48Z"},{"alias_kind":"pith_short_12","alias_value":"WPLKSI4UTADS","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"WPLKSI4UTADSKFJ5","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"WPLKSI4U","created_at":"2026-05-18T12:26:44Z"}],"graph_snapshots":[{"event_id":"sha256:64e07359c4f6074e895620824ba40c3f9070f246504d71a19ef76d262217fd95","target":"graph","created_at":"2026-05-18T02:20:48Z","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":"In this paper, we introduce a time-stampless adaptive nonuniform sampling (TANS) framework, in which time increments between samples are determined by a function of the $m$ most recent increments and sample values. Since only past samples are used in computing time increments, it is not necessary to save sampling times (time stamps) for use in the reconstruction process. We focus on two TANS schemes for discrete-time stochastic signals: a greedy method, and a method based on dynamic programming. We analyze the performances of these schemes by computing (or bounding) their trade-offs between sa","authors_text":"Muriel Medard, Soheil Feizi, Vivek K Goyal","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-10-17T19:29:39Z","title":"Time-Stampless Adaptive Nonuniform Sampling for Stochastic Signals"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.3774","kind":"arxiv","version":1},"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":"sha256:7d6ee5cc5e76716655a53dd24dcce7a8fc298c39baea9def2fdc474e34321be6","target":"record","created_at":"2026-05-18T02:20:48Z","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":"3ecf93c46ca9ca4796ba052024e7141c50c1bca93b644a407bfedf0f5c57ac48","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2011-10-17T19:29:39Z","title_canon_sha256":"166f7d894459c126182de9ca1a4c6d83afa7aee01e406c0b29fd718fb56e592e"},"schema_version":"1.0","source":{"id":"1110.3774","kind":"arxiv","version":1}},"canonical_sha256":"b3d6a92394980725153d408499a859eb7ad11da963e281490893a334132f4492","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3d6a92394980725153d408499a859eb7ad11da963e281490893a334132f4492","first_computed_at":"2026-05-18T02:20:48.095890Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:20:48.095890Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QhHQFEeYOhJVVtw4LCYHvMyo7xzdm/k6R3rZ5VLvWK4NQdePD7vl378Dgq5/kpslll92f7dmMr3wF8b9Cm/rBA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:20:48.096609Z","signed_message":"canonical_sha256_bytes"},"source_id":"1110.3774","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7d6ee5cc5e76716655a53dd24dcce7a8fc298c39baea9def2fdc474e34321be6","sha256:64e07359c4f6074e895620824ba40c3f9070f246504d71a19ef76d262217fd95"],"state_sha256":"2e084bd5fa00298356f832c56b92f10a848951e81a4f369b4c7dbf842b24f8af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p3MbvJc3ROxuWGscXj6tgifv03OEZBhfSAbTcl43D9NST4OVcRHLNRt1w9OSbCR/ESdYj/9VB3woCYmbPKKgBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T00:42:24.793943Z","bundle_sha256":"4f646460ecda9737d197ea31f49dd6e4cf94249fb01e0c0c603f4a7ec5ea4dea"}}