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Record W2099856596 · doi:10.1109/tcsii.2008.918970

A Background Sample-Time Error Calibration Technique Using Random Data for Wide-Band High-Resolution Time-Interleaved ADCs

2008· article· en· W2099856596 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

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2008
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCalibrationDynamic rangeComputer scienceSpurious-free dynamic rangeSpurious relationshipElectronic engineeringSample (material)Channel (broadcasting)SIGNAL (programming language)MathematicsTelecommunicationsEngineeringPhysicsStatistics

Abstract

fetched live from OpenAlex

Sample-time error among the channels of a time-interleaved analog-to-digital converter (ADC) is the main reason for significant degradation of the effective resolution of the high-speed time-interleaved ADC. A calibration technique for sample-time mismatches has been proposed and implemented at a low level of complexity. The calibration method uses random data and is especially suitable for ADCs used in digital data communication systems. An 800-MS/s four-channel, time-interleaved ADC system has been implemented to evaluate the performance of the technique. The experimental results show that the spurious-free dynamic range of the ADC system is improved to 58.1 dB at 350 MHz. The ADC system achieves a signal-to-noise and distortion ratio of 59.6 dB at 5 MHz and 50.1 dB at 350 MHz after calibration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.059
GPT teacher head0.251
Teacher spread0.193 · 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