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Record W2123159049 · doi:10.1109/cicc.2005.1568652

An 80-Mb/s 0.18-μm CMOS analog min-sum iterative decoder for a (32,8,10) LDPC code

2006· article· en· W2123159049 on OpenAlexaff
Saied Hemati, Amir H. Banihashemi, Calvin Plett

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsCMOSLow-density parity-check codeSubthreshold conductionDecoding methodsComputer scienceTurbo codeElectronic engineeringAnalogue electronicsElectronic circuitTransistorElectrical engineeringAlgorithmEngineeringVoltage

Abstract

fetched live from OpenAlex

Analog current-mode circuits are presented for implementing min-sum (MS) iterative decoders, which are used for decoding low-density parity-check (LDPC) codes and turbo codes. While previously reported analog decoders rely on the exponential characteristics of bipolar or subthreshold MOS transistors, proposed circuits can also be used for designing strongly inverted CMOS analog decoders. A proof-of-concept 80-Mb/s CMOS MS decoder is designed and fabricated that consumes the least reported energy per bit and operates at least six times faster than previously reported CMOS analog decoders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.331
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2006
Admission routes1
Has abstractyes

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