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Record W1917333107 · doi:10.1109/icassp.1982.1171889

Design of 2-D recursive digital filters with specified magnitude and constant group-delay responses by spectral factorization

2005· article· en· W1917333107 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
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDigital filterFactorizationTransformation (genetics)Filter (signal processing)Stability (learning theory)Constant (computer programming)Group delay and phase delayControl theory (sociology)Computer scienceMathematicsNonlinear systemMagnitude (astronomy)Group (periodic table)AlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

This paper discusses the development of an efficient, general method for the design of 2-D recursive digital filters. It effectively uses the 1-D filter theory. The technique employs the McClellan Transformation (MT). Methods are suggested for the design of McClellan Transformation Coefficients (MTC). A stability error criteria is formed on the basis of Complex Cepstrum (CC) and it guarantees the stability of the filter. Group delay and magnitude characteristics are further refined using nonlinear optimization. The method can also be used for stabilizing unstable filters. Numerical implementation and results are presented with an example.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.423

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 communication0.0000.002
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 head0.023
GPT teacher head0.237
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

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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