{ "$schema": "/api/schemas/documents.schema.json", "apiVersion": "1.0.0", "generatedAt": "2026-07-09T21:16:49.031Z", "sourcePath": "src/main/data/docs", "docId": "10.5594-M001241", "document": { "abstract": "The paper describes a board-based hardware implementation of a neural algorithm performing vector quantization for very low bit-rate video compression. The Neural Gas model has been chosen for its remarkable properties in terms of both consistency (quality of the quantization process) and easy implementation. The Neuro-board interfaces to a PC through a standard ISA bus. The system architecture is composed of a 70ns RAM bank, an FPGA-based control logic and mathematical coprocessor, and a DSP device for numerical computations. The board supports both training (codevectors adjustment) and run-time operation. The main advantages of the implemented solution lie in its simplicity and easy control for HW tests and SW development.", "abstract$meta": { "confidence": "high", "note": "Parsed from NLM article XML (_source/SMPTE/HIGHWIRE/Source Bak/smptem/10.5594_M001241.xml)", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "authors": [ { "affiliation": "Dept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy", "name": "Fabio Ancona" }, { "affiliation": "Dept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy", "name": "Stefano Rovetta" }, { "affiliation": "Dept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy", "name": "Rodolfo Zunino" } ], "authors$meta": { "confidence": "high", "note": "Object form (schema 2.3.0) migrated from string form via migrateAuthorsToObjectForm.js; bio/affiliation backfilled from _source/SMPTE/HIGHWIRE/ NLM ++", "source": "parsed", "updated": "2026-06-23T00:04:25.562Z", "version": "authors-migrate-object-form@v1" }, "contentType": "orig-research", "contentType$meta": { "confidence": "high", "note": "Canonical-confirmed full paper (summary-abstract set is orig-research in the SMPTE canonical repos); HIGHWIRE-era abstract label was a delivery artifact", "originalValue": "summary-abstract", "source": "resolved", "updated": "2026-07-09T19:12:47.628Z", "version": "contenttype-fixes@v1" }, "copyright": { "holder": "Society of Motion Picture and Television Engineers, Inc.", "holder$meta": { "confidence": "high", "note": "Parsed from NLM article XML (_source/SMPTE/HIGHWIRE/Source Bak/smptem/10.5594_M001241.xml)", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "year": "1996", "year$meta": { "confidence": "high", "note": "Parsed from NLM article XML (_source/SMPTE/HIGHWIRE/Source Bak/smptem/10.5594_M001241.xml)", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" } }, "copyright$meta": { "confidence": "high", "note": "Parsed from NLM article XML (_source/SMPTE/HIGHWIRE/Source Bak/smptem/10.5594_M001241.xml)", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "docId": "10.5594-M001241", "docId$meta": { "confidence": "high", "note": "Derived from DOI 10.5594/M001241", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "docLabel": "SMPTE Meetings and Conferences ( October 1996)", "docLabel$meta": { "confidence": "medium", "note": "Composed from venue title, volume/issue and date", "source": "inferred", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "docTitle": "Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding", "docTitle$meta": { "confidence": "high", "note": "Parsed from NLM article XML (_source/SMPTE/HIGHWIRE/Source Bak/smptem/10.5594_M001241.xml)", "source": "parsed", "updated": "2026-05-22T21:44:19.125Z", "version": "smpte-conference-paper-nlm@v1" }, "docType": "Conference Paper", "docType$meta": { "confidence": "high", "note": "NLM
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