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Record W4253412168 · doi:10.1142/s0218126600000172

2D ZERO-PHASE FIR FILTER DESIGN WITH NONUNIFORM FREQUENCY SAMPLING

2000· article· en· W4253412168 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

VenueJournal of Circuits Systems and Computers · 2000
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsConcordia University
Fundersnot available
KeywordsFinite impulse responseInterpolation (computer graphics)Filter (signal processing)Sampling (signal processing)Filter designMathematicsAlgorithmLinear phaseControl theory (sociology)Low-pass filterZero (linguistics)Phase (matter)Bivariate analysisComputer scienceStatisticsPhysicsTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, nonuniform frequency sampling techniques used in the design of two-dimensional zero-phase FIR filters are proposed and investigated. The design problem is treated as a bivariate interpolation problem with unevenly spaced data. The main idea is to select (find) sampling locations in the (ω 1 , ω 2 ) frequency plane and corresponding sample values H d (ω 1k , ω 2k ) of the desired filter frequency response such that the designed filter performance is high. Although the filters designed with the proposed techniques are not optimal, the methods are conceptually simple and produce filters with high degree of shape regularity and approximation error comparable and sometimes even smaller than the "conventional" 2D FIR filter design methods.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.740

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 communication0.0010.002
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 head0.050
GPT teacher head0.272
Teacher spread0.222 · 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