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Record W2111120985 · doi:10.1109/ccece.2007.136

A Low-Power 75dB Digitally Programmable CMOS Variable-Gain Amplifier

2007· article· en· W2111120985 on OpenAlexaff
Behnoosh Rahmatian, Shahriar Mirabbasi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVideo Graphics ArrayVariable-gain amplifierOpen-loop gainProgrammable-gain amplifierFully differential amplifierCMOSAutomatic gain controlNoise figureResistorAmplifierElectronic engineeringElectrical engineeringEngineeringOperational amplifierVoltage

Abstract

fetched live from OpenAlex

A monolithic low-power digitally programmable variable-gain amplifier (VGA) with a gain range of 75 dB is presented. The core of the design is based on a low-distortion source-degenerated differential amplifier structure. The gain is varied by changing the source-degeneration resistor as well as tuning the resistors in the common-mode feedback circuitry. The overall VGA consists of three gain stages. As a proof of concept, a 24 dB single gain stage with 2 dB gain steps is fabricated in a 0.18 mum CMOS technology. Based on the measurement results of the prototype chip, the performance of the gain stage is optimized and a three-stage 75 dB VGA is designed and simulated. The overall gain can be varied from -15 dB to 60 dB in 2.5 dB gain steps. The bandwidth of the multi-stage VGA is higher than 140 MHz and the gain error is less than 0.3 dB. The overall VGA draws 6.5 mA from a 1.8 V supply. The noise figure of the system at maximum gain is 12.5 dB, and the IIP3 at minimum gain is 14.4 dBm.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.830

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)0.0010.000

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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations16
Published2007
Admission routes1
Has abstractyes

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