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Record W1921288147 · doi:10.1002/cta.2011

Analytical synthesis of voltage‐mode even/odd‐nth‐order differential difference current conveyor and fully differential current conveyor II‐grounded resistor and capacitor universal filter structures

2014· article· en· W1921288147 on OpenAlexaff
Chun‐Ming Chang, M.N.S. Swamy, Ahmed M. Soliman

Bibliographic record

VenueInternational Journal of Circuit Theory and Applications · 2014
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsConcordia University
Fundersnot available
KeywordsCurrent conveyorResistorFilter (signal processing)Control theory (sociology)Active filterBand-pass filterLow-pass filterTransfer functionVoltageSpiceMathematicsHigh-pass filterElectronic engineeringComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Summary A complete definition of an odd/even‐nth‐order notch or band‐reject filter transfer function is presented. Based on the differences between the input voltage and (i) an nth‐order high‐pass; (ii) a traditional nth‐order notch; and (iii) an nth‐order all‐pass filtering transfer function, a systematic method has been proposed to derive a universal filter structure that can realize voltage‐mode odd/even‐nth‐order low‐pass, band‐pass, high‐pass, all‐pass and traditional notch filters. The intrinsic capability of voltage‐mode addition and subtraction of the two active elements, differential difference current conveyors and fully differential current conveyors, is used to advantage in the aforementioned synthesis procedure. Based upon the definition of an nth‐order notch or band‐reject filter transfer function proposed in this paper, the aforementioned universal one has been further extended to the newly defined nth‐order band rejection filter. The voltage and current tracking errors of the two active elements are compensated by varying the resistances of the proposed filter. Filtering feasibility, stability, component sensitivities, linear and dynamic ranges, power consumption, and noise are simulated using H‐Spice with 0.35 µm process. Compared to some of the recently reported universal biquads, the new one is shown to enjoy the lowest component sensitivities and the best output accuracy for all‐pass signals. Moreover, Monte Carlo and two‐tone tests for intermodulation linearity simulations are also investigated. Copyright © 2014 John Wiley & Sons, Ltd.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.242
Teacher spread0.231 · 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 designSimulation or modeling
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

Citations15
Published2014
Admission routes1
Has abstractyes

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