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Record W1699860908 · doi:10.1109/iscas.2003.1205570

A new differential CMOS current pre-amplifier for optical communications

2003· article· en· W1699860908 on OpenAlexaff
Bendong Sun, Fei Yuan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFully differential amplifierDirect-coupled amplifierElectrical engineeringCurrent mirrorCommon-mode rejection ratioCMOSAmplifierCommon sourceTransistorCurrent-feedback operational amplifierOperational transconductance amplifierDifferential amplifierOperational amplifierElectronic engineeringPhysicsEngineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a new low-voltage fully differential CMOS current-mode pre-amplifier for optical communications. The number of transistors between the power and ground rails is minimum so that the minimum supply voltage is only V/sub T/ + V/sub sat/. The pre-amplifier is a balanced two-stage configuration such that the effect of bias-dependent. mismatches is minimized. This configuration also achieves wide bandwidth and high current gain with reduced power consumption and transistor sizes. To lower the input impedance and increase the bandwidth, a new differential current-current negative feedback is introduced. In addition, a current-current common-mode feedback is employed to increase the common-mode rejection ratio (CMRR). The pre-amplifier is designed using a 0.18 /spl mu/m 1.8 V CMOS technology. Simulation results from SPICE demonstrate that with a 0.5 pF photo diode capacitance, the pre-amplifier provides 31 dB current gain or equivalently 65 dB trans-impedance gain at 2.53 GHz.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.040
GPT teacher head0.282
Teacher spread0.241 · 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
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

Citations3
Published2003
Admission routes1
Has abstractyes

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