{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:REGOQQN4FE6NP7WGA6YYYODGCJ","short_pith_number":"pith:REGOQQN4","schema_version":"1.0","canonical_sha256":"890ce841bc293cd7fec607b18c3866126ed6639140db1876875be3bf21fb7b24","source":{"kind":"arxiv","id":"2606.29099","version":1},"attestation_state":"computed","paper":{"title":"Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad","submitted_at":"2026-06-27T21:59:01Z","abstract_excerpt":"Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal processing, yet both paradigms face limitations when value encoding and timing dynamics must be learned within a single computational structure. This paper introduces a network based on Unified Complex-valued Neuron (UCN), a new neural computational model that integrates continuous activation and phase-driven event generation through an asymmetric complex-valued state. In the UCN, magnitude encodes signal strength while phase governs intrinsic te"},"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":"2606.29099","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-06-27T21:59:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ff51741da9945e8cac8bc61f6a99079ad7a1946e74385fbac1af4095c0f18c41","abstract_canon_sha256":"f55089b982cbba3a2efa7a554d92e5af76969e03ae0998af9f356271e18afa48"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:17:52.853979Z","signature_b64":"yEPS78v2TjMm+7WrkMpkmVe+UwBagNQ1W38LWVcoft4f2s8vwtQ7sKnIvJyzVZAZ79im0DNh8rZOrfqnADGgBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"890ce841bc293cd7fec607b18c3866126ed6639140db1876875be3bf21fb7b24","last_reissued_at":"2026-06-30T01:17:52.853311Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:17:52.853311Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad","submitted_at":"2026-06-27T21:59:01Z","abstract_excerpt":"Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal processing, yet both paradigms face limitations when value encoding and timing dynamics must be learned within a single computational structure. This paper introduces a network based on Unified Complex-valued Neuron (UCN), a new neural computational model that integrates continuous activation and phase-driven event generation through an asymmetric complex-valued state. In the UCN, magnitude encodes signal strength while phase governs intrinsic te"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29099","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.29099/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2606.29099","created_at":"2026-06-30T01:17:52.853419+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.29099v1","created_at":"2026-06-30T01:17:52.853419+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29099","created_at":"2026-06-30T01:17:52.853419+00:00"},{"alias_kind":"pith_short_12","alias_value":"REGOQQN4FE6N","created_at":"2026-06-30T01:17:52.853419+00:00"},{"alias_kind":"pith_short_16","alias_value":"REGOQQN4FE6NP7WG","created_at":"2026-06-30T01:17:52.853419+00:00"},{"alias_kind":"pith_short_8","alias_value":"REGOQQN4","created_at":"2026-06-30T01:17:52.853419+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/REGOQQN4FE6NP7WGA6YYYODGCJ","json":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ.json","graph_json":"https://pith.science/api/pith-number/REGOQQN4FE6NP7WGA6YYYODGCJ/graph.json","events_json":"https://pith.science/api/pith-number/REGOQQN4FE6NP7WGA6YYYODGCJ/events.json","paper":"https://pith.science/paper/REGOQQN4"},"agent_actions":{"view_html":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ","download_json":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ.json","view_paper":"https://pith.science/paper/REGOQQN4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.29099&json=true","fetch_graph":"https://pith.science/api/pith-number/REGOQQN4FE6NP7WGA6YYYODGCJ/graph.json","fetch_events":"https://pith.science/api/pith-number/REGOQQN4FE6NP7WGA6YYYODGCJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ/action/storage_attestation","attest_author":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ/action/author_attestation","sign_citation":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ/action/citation_signature","submit_replication":"https://pith.science/pith/REGOQQN4FE6NP7WGA6YYYODGCJ/action/replication_record"}},"created_at":"2026-06-30T01:17:52.853419+00:00","updated_at":"2026-06-30T01:17:52.853419+00:00"}