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Record W2041347804 · doi:10.1109/iscas.2012.6271415

Compact chopper-stabilized neural amplifier with low-distortion high-pass filter in 0.13µm CMOS

2012· article· en· W2041347804 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTotal harmonic distortionCMOSAmplifierDifferential amplifierFlicker noiseOperational amplifierAnalogue filterElectrical engineeringCapacitorLow-pass filterInstrumentation amplifierElectronic engineeringNoise (video)Computer sciencePhysicsFilter (signal processing)EngineeringNoise figureVoltageArtificial intelligenceDigital filter

Abstract

fetched live from OpenAlex

A compact and low-distortion neural recording amplifier is presented. The amplifier consists of two stages of amplification using capacitive feedback to set a gain of 54dB. To minimize flicker noise in the 1st stage, internal chopping is utilized at the folded node of the OTA, resulting in flicker noise contribution from the input differential pair only. A low-distortion constant-V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GS</inf> feedback circuit to set a low frequency high-pass pole is introduced. It is less sensitive to the output swing than the conventional sub-threshold MOS circuit. The amplifier fabricated in a standard 1.2V 0.13µm CMOS technology occupies 125×175µm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and achieves an NEF of 4.4, an input-referred noise of 4.7µV over a 5kHz bandwidth, a CMRR of 75dB and a THD of −50dB for a 0.6V output swing.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.762

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 communication0.0000.001
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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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