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Record W2176339269 · doi:10.1109/esscirc.2007.4430270

A high bandwidth power scaleable sub-sampling 10-bit pipelined ADC with embedded sample and hold

2007· article· en· W2176339269 on OpenAlexaff
Imran Ahmed, D.A. Johns

Bibliographic record

VenueProceedings of ESSCIRC · 2007
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBandwidth (computing)CMOSComputer scienceSample (material)Electrical engineeringEngineeringTelecommunicationsChemistryChromatography

Abstract

fetched live from OpenAlex

A pipelined ADC architecture for use in sub-sampled systems which has its power scaleable with down sampled bandwidth is presented. Using a technique developed to eliminate the front end sample and hold, a power savings of >20% is achieved compared to a previous design. A technique to improve the settling behavior of Rapid Power on Opamps is also presented. Measured results in 1.8V 0.18μm CMOS verify the removal of the front end sample and hold does not cause gross MSB errors for input frequencies higher than 267MHz. With fs=50MS/s, for fin=79MHz the SNDR is 51.5dB, and with fs=4.55MS/s for fin= 267MHz the SNDR is 52.2dB.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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
GenreMethods

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

Citations8
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of ESSCIRCSame topicAnalog and Mixed-Signal Circuit DesignFrench-language works237,207