{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:GD3TVTUNN5EZTYSV4ILYQ34NRL","short_pith_number":"pith:GD3TVTUN","canonical_record":{"source":{"id":"1703.10381","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-30T09:43:35Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"05e5c1d5b961d1b8f0f71042ac260b895fae09c042eb58930096680f7f14488c","abstract_canon_sha256":"417ffe1869950f90780317fb79d0cbab0b855e5eb8ee456b0a65e0b5407f535d"},"schema_version":"1.0"},"canonical_sha256":"30f73ace8d6f4999e255e217886f8d8af208b0d75df35219a152360598f80e65","source":{"kind":"arxiv","id":"1703.10381","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.10381","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"arxiv_version","alias_value":"1703.10381v1","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.10381","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"pith_short_12","alias_value":"GD3TVTUNN5EZ","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"GD3TVTUNN5EZTYSV","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"GD3TVTUN","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:GD3TVTUNN5EZTYSV4ILYQ34NRL","target":"record","payload":{"canonical_record":{"source":{"id":"1703.10381","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-30T09:43:35Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"05e5c1d5b961d1b8f0f71042ac260b895fae09c042eb58930096680f7f14488c","abstract_canon_sha256":"417ffe1869950f90780317fb79d0cbab0b855e5eb8ee456b0a65e0b5407f535d"},"schema_version":"1.0"},"canonical_sha256":"30f73ace8d6f4999e255e217886f8d8af208b0d75df35219a152360598f80e65","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:14.128286Z","signature_b64":"n7Vm6+s4/W3V3IphnU40EQXoioywWvCi3NONbz3SdP8rcOPTFg2dxBlDf2DprrnVuQ4OkzjBDxPJf2K/XjJTDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30f73ace8d6f4999e255e217886f8d8af208b0d75df35219a152360598f80e65","last_reissued_at":"2026-05-18T00:36:14.127705Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:14.127705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.10381","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":"2026-05-18T00:36:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LFyRGTZYx2pmCwT9YRs19SaM7imAxSeuq0A5/EFboCHPp7BM7pR28Ea/59ym1Z+6h0he/xle2fL/dgwAgqmdDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:03:25.872215Z"},"content_sha256":"fd0545073bfd290f2813b3865d04140e80950534769be5c91ea317997e42d495","schema_version":"1.0","event_id":"sha256:fd0545073bfd290f2813b3865d04140e80950534769be5c91ea317997e42d495"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:GD3TVTUNN5EZTYSV4ILYQ34NRL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Blind source separation of tensor-valued time series","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Joni Virta, Klaus Nordhausen","submitted_at":"2017-03-30T09:43:35Z","abstract_excerpt":"The blind source separation model for multivariate time series generally assumes that the observed series is a linear transformation of an unobserved series with temporally uncorrelated or independent components. Given the observations, the objective is to find a linear transformation that recovers the latent series. Several methods for accomplishing this exist and three particular ones are the classic SOBI and the recently proposed generalized FOBI (gFOBI) and generalized JADE (gJADE), each based on the use of joint lagged moments. In this paper we generalize the methodologies behind these al"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.10381","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":"2026-05-18T00:36:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rt0Rftlb+9u61vSERh+xPQu4odAUl5DXRmDZzMFvLhLxxtqNhmI8iwzVV8VWzEsOPA6z8ouq85PLTiS5vO8cBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:03:25.872903Z"},"content_sha256":"65cad6b05af5e4310fc8af63ad2d11e5659012614c389052682b2b8c856060b6","schema_version":"1.0","event_id":"sha256:65cad6b05af5e4310fc8af63ad2d11e5659012614c389052682b2b8c856060b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/bundle.json","state_url":"https://pith.science/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/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":"2026-05-31T15:03:25Z","links":{"resolver":"https://pith.science/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL","bundle":"https://pith.science/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/bundle.json","state":"https://pith.science/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GD3TVTUNN5EZTYSV4ILYQ34NRL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GD3TVTUNN5EZTYSV4ILYQ34NRL","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":"417ffe1869950f90780317fb79d0cbab0b855e5eb8ee456b0a65e0b5407f535d","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-30T09:43:35Z","title_canon_sha256":"05e5c1d5b961d1b8f0f71042ac260b895fae09c042eb58930096680f7f14488c"},"schema_version":"1.0","source":{"id":"1703.10381","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.10381","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"arxiv_version","alias_value":"1703.10381v1","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.10381","created_at":"2026-05-18T00:36:14Z"},{"alias_kind":"pith_short_12","alias_value":"GD3TVTUNN5EZ","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"GD3TVTUNN5EZTYSV","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"GD3TVTUN","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:65cad6b05af5e4310fc8af63ad2d11e5659012614c389052682b2b8c856060b6","target":"graph","created_at":"2026-05-18T00:36:14Z","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":"The blind source separation model for multivariate time series generally assumes that the observed series is a linear transformation of an unobserved series with temporally uncorrelated or independent components. Given the observations, the objective is to find a linear transformation that recovers the latent series. Several methods for accomplishing this exist and three particular ones are the classic SOBI and the recently proposed generalized FOBI (gFOBI) and generalized JADE (gJADE), each based on the use of joint lagged moments. In this paper we generalize the methodologies behind these al","authors_text":"Joni Virta, Klaus Nordhausen","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-30T09:43:35Z","title":"Blind source separation of tensor-valued time series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.10381","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:fd0545073bfd290f2813b3865d04140e80950534769be5c91ea317997e42d495","target":"record","created_at":"2026-05-18T00:36:14Z","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":"417ffe1869950f90780317fb79d0cbab0b855e5eb8ee456b0a65e0b5407f535d","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-30T09:43:35Z","title_canon_sha256":"05e5c1d5b961d1b8f0f71042ac260b895fae09c042eb58930096680f7f14488c"},"schema_version":"1.0","source":{"id":"1703.10381","kind":"arxiv","version":1}},"canonical_sha256":"30f73ace8d6f4999e255e217886f8d8af208b0d75df35219a152360598f80e65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30f73ace8d6f4999e255e217886f8d8af208b0d75df35219a152360598f80e65","first_computed_at":"2026-05-18T00:36:14.127705Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:14.127705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n7Vm6+s4/W3V3IphnU40EQXoioywWvCi3NONbz3SdP8rcOPTFg2dxBlDf2DprrnVuQ4OkzjBDxPJf2K/XjJTDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:14.128286Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.10381","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd0545073bfd290f2813b3865d04140e80950534769be5c91ea317997e42d495","sha256:65cad6b05af5e4310fc8af63ad2d11e5659012614c389052682b2b8c856060b6"],"state_sha256":"ae673c17dec3ec557d534ac3118bb59d72d5e587eeb931d5d2366433b3ffccec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KQzc1l5ICXpEc1JYvva6pXgZ9C5M+t96n6a5mtaJ/1E9vS5tZFmdPO+kTBoTv7V0KRUDfra9fXhXWFHTkmuQAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T15:03:25.877092Z","bundle_sha256":"3523e733686f23311ab08c2e8744164bd8f4c6b6b110ca71f7cb8a8ade4bfaa8"}}