{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11295212","patent":{"patent_number":"US-11295212","title":"Deep neural networks via physical electromagnetics simulator","assignee":null,"inventors":[],"filing_date":"2019-04-23T00:00:00.000Z","publication_date":"2022-04-05T00:00:00.000Z","cpc_codes":["G06N","G06N","G06N","G06N","G06N","G06N","G06N"],"num_claims":23,"abstract":"A system for physically simulating a neural network is described herein. The system includes a plurality of physical voxels configurable to represent nodes of the neural network operating in response to electromagnetic radiation. Each of the physical voxels includes an impedance adjuster, a field detector, and a signal adjuster. The impedance adjuster adjusts impedance to the electromagnetic radiation within a corresponding one of the physical voxels. Weights between nodes of the neural network are based on the adjusted impedance. The field detector measures local field response within the corresponding one of the physical voxels. The local field response is representative of the electromagnetic radiation with the adjusted impedance. The signal adjuster is coupled to receive the local field response and apply an adjustment to the received local field response. The adjustment corresponds to an activation function of the neural network at the corresponding one of the physical voxels."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Deep neural networks via physical electromagnetics simulator","description":"A system for physically simulating a neural network is described herein. The system includes a plurality of physical voxels configurable to represent nodes of the neural network operating in response ","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11295212","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11295212","citation_suggestion":"Patentable. \"Deep neural networks via physical electromagnetics simulator\" (US-11295212). https://patentable.app/patents/US-11295212","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11295212","json":"https://patentable.app/api/llm-context/US-11295212","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T16:22:57.713Z"}