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Record W2146313082 · doi:10.1108/13565360710745584

A useful pseudo‐logarithmic circuit

2007· article· en· W2146313082 on OpenAlexaff
Brent Maundy, David T. Westwick, Stephan J. G. Gift

Bibliographic record

VenueMicroelectronics International · 2007
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsResistorOperational amplifierLogarithmLog amplifierCompandingElectronic circuitCircuit designElectronic engineeringAmplifierDiscrete circuitBlock (permutation group theory)Computer scienceElectrical engineeringFunction (biology)PiecewiseControl theory (sociology)Equivalent circuitEngineeringMathematicsCMOSControl (management)

Abstract

fetched live from OpenAlex

Purpose This paper proposes a useful pseudo‐logarithmic circuit as a basic building block in the construction of a logarithmic amplifier made from piecewise approximations. Design/methodology/approach The circuit employs two operational and a handful of resistors, and mimics the logarithmic function over a predefined range. Control of the pseudo‐logarithmic function is achieved by a ratio of resistances defined as x , one of which may be digitally switched, or implemented by tunable transconductors. When controlled by digitally switched resistors, the circuit is particularly attractive because of the commercial availability of such resistors, and with the aid of simple control logic, individual blocks can be algebraically summed to extend the dynamic range of the basic pseudo‐logarithmic block which is 28 dB Findings Experimental results using off the shelf operational amplifiers (opamps) and a handful of resistors show that the circuit yields a maximum log error of 0.6915 dB for x in (0.22, 4.65). Originality/value Proposes a novel circuit capable of realizing the pseudo‐logarithmic function ( x −1)/(1+ x ). The circuit is simple and easily implemented using readily available opamps.

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 score0.890
Threshold uncertainty score0.797

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)0.0000.000

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 head0.009
GPT teacher head0.211
Teacher spread0.201 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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