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Record W2184235334 · doi:10.5755/j02.eie.10744

Estimation of Frequency Characteristics of Super-Narrow Band Digital Filters

2007· article· en· W2184235334 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

VenueElektronika ir Elektrotechnika · 2007
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsTransport Canada
Fundersnot available
KeywordsFast Fourier transformImpulse (physics)Computer scienceFrequency bandTransformation (genetics)AlgorithmImpulse responseDigital filterFourier transformFinite impulse responseArithmeticElectronic engineeringMathematicsFilter (signal processing)TelecommunicationsEngineeringBandwidth (computing)Computer vision

Abstract

fetched live from OpenAlex

The verification of frequency characteristics of narrow-band biline structures is rather problematic. The traditional way of an estimation of dynamic frequency characteristics by the impulse response (IR) is inconvenient in this case because of its excessively big demanded length. It does not allow investigating the frequency characteristics with necessary accuracy by means of fast Fourier transformation (FFT). The last one brings practically unpredictable errors because of insufficient precision of machine arithmetic and excessively big number of demanded arithmetic operations. The new method of verification of frequency characteristics of recursive narrow-band systems is offered. The problem of a choice of necessary duration of the corresponding impulse response and criteria of its maximum deviation from ideal is being discussed. The examples of correct verification of dynamic characteristics are shown. Ill. 5, bibl. 9 (in English; summaries in English, Russian and Lithuanian).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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