{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:TEDLPGNWZ2WLVLNBVYLVOOCPHJ","short_pith_number":"pith:TEDLPGNW","canonical_record":{"source":{"id":"1407.6404","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2014-07-23T22:53:20Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"1a9d272b486f6be8c80b3b6d40188f4abfcbde49fdf56c1174d7f5fbdd481f47","abstract_canon_sha256":"4a1a835b543edf10ba7f7b46195a14faca2d263666e10a45640cb8f0c18cd2d5"},"schema_version":"1.0"},"canonical_sha256":"9906b799b6ceacbaada1ae1757384f3a40d2ef83dc60898d5fe4f146260571ae","source":{"kind":"arxiv","id":"1407.6404","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.6404","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"arxiv_version","alias_value":"1407.6404v2","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.6404","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"pith_short_12","alias_value":"TEDLPGNWZ2WL","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_16","alias_value":"TEDLPGNWZ2WLVLNB","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_8","alias_value":"TEDLPGNW","created_at":"2026-05-18T12:28:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:TEDLPGNWZ2WLVLNBVYLVOOCPHJ","target":"record","payload":{"canonical_record":{"source":{"id":"1407.6404","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2014-07-23T22:53:20Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"1a9d272b486f6be8c80b3b6d40188f4abfcbde49fdf56c1174d7f5fbdd481f47","abstract_canon_sha256":"4a1a835b543edf10ba7f7b46195a14faca2d263666e10a45640cb8f0c18cd2d5"},"schema_version":"1.0"},"canonical_sha256":"9906b799b6ceacbaada1ae1757384f3a40d2ef83dc60898d5fe4f146260571ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:47.290695Z","signature_b64":"Z7Sk+ZHIZsqBoF249uYQOa3V5cpyF6IznTVWhq4KNAjzRa3uGtAIrAn2wkFnAS3vsCxaYfq2WcrqtUmcdcpzDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9906b799b6ceacbaada1ae1757384f3a40d2ef83dc60898d5fe4f146260571ae","last_reissued_at":"2026-05-18T01:17:47.289922Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:47.289922Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1407.6404","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":"2026-05-18T01:17:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OyJmqzoJpTzmPhGv5LlajhmkiAPAoLVOzNaHH1xrDt1ep+AXHKzGO1AuhIS/pBo1pxkesQzzFdN5T1t7uO0kAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T22:47:23.926259Z"},"content_sha256":"38750d4973a4696e140097facd0056a4c55bc15657c650386764fdc2e62bad27","schema_version":"1.0","event_id":"sha256:38750d4973a4696e140097facd0056a4c55bc15657c650386764fdc2e62bad27"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:TEDLPGNWZ2WLVLNBVYLVOOCPHJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An autoregressive (AR) model based stochastic unknown input realization and filtering technique","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"math.DS","authors_text":"Dan Yu, Suman Chakravorty","submitted_at":"2014-07-23T22:53:20Z","abstract_excerpt":"This paper studies the state estimation problem of linear discrete-time systems with stochastic unknown inputs. The unknown input is a wide-sense stationary process while no other prior informaton needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input statistics from the output data by solving an appropriate least squares problem, then fit an AR model to the recovered input statistics and construct an innovations model of the unknown inputs using the eigensystem realization algorithm (ERA). An augmented state sy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.6404","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":"2026-05-18T01:17:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OY5jNUtujLocuuiVe6WggShS/5m9hfzy6geQtK7A0OS8UreGp1vyed5edIoslQQTj56Xo7h5d7iZudax1lCwBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T22:47:23.926886Z"},"content_sha256":"a58c0e8cc6811d95c448c17a596ea67bcfee7669634e5fea565ce73429111a1c","schema_version":"1.0","event_id":"sha256:a58c0e8cc6811d95c448c17a596ea67bcfee7669634e5fea565ce73429111a1c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/bundle.json","state_url":"https://pith.science/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/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":"2026-05-21T22:47:23Z","links":{"resolver":"https://pith.science/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ","bundle":"https://pith.science/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/bundle.json","state":"https://pith.science/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TEDLPGNWZ2WLVLNBVYLVOOCPHJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:TEDLPGNWZ2WLVLNBVYLVOOCPHJ","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":"4a1a835b543edf10ba7f7b46195a14faca2d263666e10a45640cb8f0c18cd2d5","cross_cats_sorted":["cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2014-07-23T22:53:20Z","title_canon_sha256":"1a9d272b486f6be8c80b3b6d40188f4abfcbde49fdf56c1174d7f5fbdd481f47"},"schema_version":"1.0","source":{"id":"1407.6404","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.6404","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"arxiv_version","alias_value":"1407.6404v2","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.6404","created_at":"2026-05-18T01:17:47Z"},{"alias_kind":"pith_short_12","alias_value":"TEDLPGNWZ2WL","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_16","alias_value":"TEDLPGNWZ2WLVLNB","created_at":"2026-05-18T12:28:49Z"},{"alias_kind":"pith_short_8","alias_value":"TEDLPGNW","created_at":"2026-05-18T12:28:49Z"}],"graph_snapshots":[{"event_id":"sha256:a58c0e8cc6811d95c448c17a596ea67bcfee7669634e5fea565ce73429111a1c","target":"graph","created_at":"2026-05-18T01:17:47Z","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":"This paper studies the state estimation problem of linear discrete-time systems with stochastic unknown inputs. The unknown input is a wide-sense stationary process while no other prior informaton needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input statistics from the output data by solving an appropriate least squares problem, then fit an AR model to the recovered input statistics and construct an innovations model of the unknown inputs using the eigensystem realization algorithm (ERA). An augmented state sy","authors_text":"Dan Yu, Suman Chakravorty","cross_cats":["cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2014-07-23T22:53:20Z","title":"An autoregressive (AR) model based stochastic unknown input realization and filtering technique"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.6404","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":"sha256:38750d4973a4696e140097facd0056a4c55bc15657c650386764fdc2e62bad27","target":"record","created_at":"2026-05-18T01:17:47Z","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":"4a1a835b543edf10ba7f7b46195a14faca2d263666e10a45640cb8f0c18cd2d5","cross_cats_sorted":["cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2014-07-23T22:53:20Z","title_canon_sha256":"1a9d272b486f6be8c80b3b6d40188f4abfcbde49fdf56c1174d7f5fbdd481f47"},"schema_version":"1.0","source":{"id":"1407.6404","kind":"arxiv","version":2}},"canonical_sha256":"9906b799b6ceacbaada1ae1757384f3a40d2ef83dc60898d5fe4f146260571ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9906b799b6ceacbaada1ae1757384f3a40d2ef83dc60898d5fe4f146260571ae","first_computed_at":"2026-05-18T01:17:47.289922Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:17:47.289922Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z7Sk+ZHIZsqBoF249uYQOa3V5cpyF6IznTVWhq4KNAjzRa3uGtAIrAn2wkFnAS3vsCxaYfq2WcrqtUmcdcpzDg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:17:47.290695Z","signed_message":"canonical_sha256_bytes"},"source_id":"1407.6404","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:38750d4973a4696e140097facd0056a4c55bc15657c650386764fdc2e62bad27","sha256:a58c0e8cc6811d95c448c17a596ea67bcfee7669634e5fea565ce73429111a1c"],"state_sha256":"b685ff8be718fb3c50faa0f5ea2387adbdc962c98c0d962495d53a7e5738f6da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qs+xRbWpRjB5kIHsleFdh3LQIJWnDKeoumQgArngPbqxRO94dOofUPCgGsvstFD+Lx8xXTpl+KmHYbVBauO1AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T22:47:23.930235Z","bundle_sha256":"08b7bc18f1918dd5703da6ce77f51ae7074427fca0387822990297e7e2f3b9d8"}}