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Record W2108938119 · doi:10.1109/iscas.2000.858860

A novel mixed-mode adaptive equalization system for high-speed 2-level PAM signals

2002· article· en· W2108938119 on OpenAlex
D.H.S. Tam, Wai Tung Ng

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFinite impulse responseComputer scienceDigital filterAdaptive filterElectronic engineeringCMOSFilter (signal processing)Equalization (audio)Impulse (physics)EngineeringAlgorithmPhysics

Abstract

fetched live from OpenAlex

A novel mixed-mode adaptive equalization system for a high-speed 2-level pulse-amplitude nodulated (PAM) signal is presented. The intended application is in the area of digital serial interface, such as a non-return-to-zero-inverted (NRZI) serial video signal with a data rate of 270 Mbits/s. The adaptive system tunes the zeros of a finite-impulse-response (FIR) analog programmable filter. Programmable differentiators and transconductors are designed to increase the tuning range of the filter. An average error, obtained by calculating the accumulated area of the eye-diagram, and average gradients are proposed as inputs to a digital least-mean-squared (LMS) algorithm. This approach allows a more relaxed speed requirement for analog-to-digital converters (ADCs). A third-order analog filter, along with some essential circuit blocks, are designed for a 0.35 /spl mu/m CMOS 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.748
Threshold uncertainty score0.975

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 communication0.0000.000
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 head0.071
GPT teacher head0.266
Teacher spread0.195 · 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

Citations1
Published2002
Admission routes2
Has abstractyes

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