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Record W2099484109 · doi:10.1109/ccece.2004.1349615

Implementing a digitally synthesized adaptive pre-emphasis algorithm for use in a high-speed backplane interconnection

2004· article· en· W2099484109 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsApplication-specific integrated circuitComputer scienceVery-large-scale integrationEmphasis (telecommunications)InterconnectionBackplaneCMOSStandard cellElectronic engineeringDigital electronicsSimple (philosophy)FootprintModulation (music)Integrated circuit layoutElectronic circuitComputer architectureIntegrated circuitEmbedded systemComputer hardwareEngineeringElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a novel implementation technique using simple digital ASIC synthesis to generate a silicon layout of a multi-level PAM modulation circuit that incorporates a digitally adaptive pre-emphasis scheme. While computationally complex, the actual VLSI implementation is relatively simple, requires minimal power and generates a layout that minimizes the footprint. The results of the digital synthesis of several comparable adaptive circuits are detailed and compared. Several devices have been submitted for fabrication, via CMC, using the TSMC 0.18 /spl mu/m CMOS generic standard cell process.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.254
Teacher spread0.233 · 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

Quick stats

Citations3
Published2004
Admission routes1
Has abstractyes

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