{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:SJNJVIB6ZPXFCNBUZN4SMMBRHW","short_pith_number":"pith:SJNJVIB6","schema_version":"1.0","canonical_sha256":"925a9aa03ecbee513434cb792630313da68a271812b9cf8b996752992ca6225a","source":{"kind":"arxiv","id":"1211.6631","version":1},"attestation_state":"computed","paper":{"title":"Asymptotic Properties of Likelihood Based Linear Modulation Classification Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","stat.AP"],"primary_cat":"cs.IT","authors_text":"Andrew L. Drozd, Onur Ozdemir, Pramod K. Varshney, Wei Su","submitted_at":"2012-11-28T15:22:29Z","abstract_excerpt":"The problem of linear modulation classification using likelihood based methods is considered. Asymptotic properties of most commonly used classifiers in the literature are derived. These classifiers are based on hybrid likelihood ratio test (HLRT) and average likelihood ratio test (ALRT), respectively. Both a single-sensor setting and a multi-sensor setting that uses a distributed decision fusion approach are analyzed. For a modulation classification system using a single sensor, it is shown that HLRT achieves asymptotically vanishing probability of error (Pe) whereas the same result cannot be"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1211.6631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2012-11-28T15:22:29Z","cross_cats_sorted":["math.IT","stat.AP"],"title_canon_sha256":"f1e2b5ba1e4d855123bcf1a02d8b0deb6eb6ad1e915e7e9ac0e70817004010a1","abstract_canon_sha256":"0e7922909baa4cc47ce04d3158f9285b9fc46edd81311281a972197408c1c280"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:39:44.154817Z","signature_b64":"84eIXep9JNhDoQjYu03cI1pJ3XHR/8+4SNFpzUldJG8TtWdCnjw3Apa4n/1vLS1DHZwOY/11CaBNEBm83ktnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"925a9aa03ecbee513434cb792630313da68a271812b9cf8b996752992ca6225a","last_reissued_at":"2026-05-18T03:39:44.154217Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:39:44.154217Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Asymptotic Properties of Likelihood Based Linear Modulation Classification Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","stat.AP"],"primary_cat":"cs.IT","authors_text":"Andrew L. Drozd, Onur Ozdemir, Pramod K. Varshney, Wei Su","submitted_at":"2012-11-28T15:22:29Z","abstract_excerpt":"The problem of linear modulation classification using likelihood based methods is considered. Asymptotic properties of most commonly used classifiers in the literature are derived. These classifiers are based on hybrid likelihood ratio test (HLRT) and average likelihood ratio test (ALRT), respectively. Both a single-sensor setting and a multi-sensor setting that uses a distributed decision fusion approach are analyzed. For a modulation classification system using a single sensor, it is shown that HLRT achieves asymptotically vanishing probability of error (Pe) whereas the same result cannot be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1211.6631","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1211.6631","created_at":"2026-05-18T03:39:44.154295+00:00"},{"alias_kind":"arxiv_version","alias_value":"1211.6631v1","created_at":"2026-05-18T03:39:44.154295+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1211.6631","created_at":"2026-05-18T03:39:44.154295+00:00"},{"alias_kind":"pith_short_12","alias_value":"SJNJVIB6ZPXF","created_at":"2026-05-18T12:27:20.899486+00:00"},{"alias_kind":"pith_short_16","alias_value":"SJNJVIB6ZPXFCNBU","created_at":"2026-05-18T12:27:20.899486+00:00"},{"alias_kind":"pith_short_8","alias_value":"SJNJVIB6","created_at":"2026-05-18T12:27:20.899486+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW","json":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW.json","graph_json":"https://pith.science/api/pith-number/SJNJVIB6ZPXFCNBUZN4SMMBRHW/graph.json","events_json":"https://pith.science/api/pith-number/SJNJVIB6ZPXFCNBUZN4SMMBRHW/events.json","paper":"https://pith.science/paper/SJNJVIB6"},"agent_actions":{"view_html":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW","download_json":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW.json","view_paper":"https://pith.science/paper/SJNJVIB6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1211.6631&json=true","fetch_graph":"https://pith.science/api/pith-number/SJNJVIB6ZPXFCNBUZN4SMMBRHW/graph.json","fetch_events":"https://pith.science/api/pith-number/SJNJVIB6ZPXFCNBUZN4SMMBRHW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW/action/storage_attestation","attest_author":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW/action/author_attestation","sign_citation":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW/action/citation_signature","submit_replication":"https://pith.science/pith/SJNJVIB6ZPXFCNBUZN4SMMBRHW/action/replication_record"}},"created_at":"2026-05-18T03:39:44.154295+00:00","updated_at":"2026-05-18T03:39:44.154295+00:00"}