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Record W1515985170 · doi:10.1109/iscas.1990.112513

A method for the design of a class of 2-D IIR variable cutoff boundary filters

2002· article· en· W1515985170 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
KeywordsInfinite impulse responseMathematicsCutoffVariable (mathematics)Boundary (topology)Separable spaceTransfer function2D FiltersMathematical analysisClass (philosophy)Function (biology)Applied mathematicsDiscrete mathematicsAlgorithmDigital filterComputer scienceFilter (signal processing)Physics

Abstract

fetched live from OpenAlex

A method of designing a class of 2-D IIR (infinite-impulse-response) filters with a variable cutoff boundary is presented. The transfer function of this class of 2-D filters has a zero-phase two-variable polynomial in z/sub 1/ and z/sub 2/ in the numerator and two separable polynomials (D/sub 1/(z/sub 1/), D/sub 2/(z/sub 2/)) in the denominator. The transformations used for changing the cutoff boundary are A.V. Oppenheim's (1976) for the numerator and spectral transformations for the denominator of the transfer function. It is demonstrated that the proposed method results in 2-D filters having better circular contours than the existing techniques. This technique also allows one to perform circular-to-elliptic transformation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.911
Threshold uncertainty score0.198

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 science0.0010.000
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 head0.077
GPT teacher head0.301
Teacher spread0.224 · 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
Published2002
Admission routes1
Has abstractyes

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