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Record W1711307746 · doi:10.1109/iscas.2006.1693733

Design of a multidimensional split vector-radix decimation-in-frequency FFT algorithm

2006· article· en· W1711307746 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 institutionsConcordia University
Fundersnot available
KeywordsFast Fourier transformSplit-radix FFT algorithmPrime-factor FFT algorithmDecimationRadix (gastropod)AlgorithmTwiddle factorDimension (graph theory)Computer scienceRader's FFT algorithmKronecker productDiscrete Fourier transform (general)MathematicsKronecker deltaFourier transformFilter (signal processing)Fourier analysisFractional Fourier transformCombinatorics

Abstract

fetched live from OpenAlex

In this paper, the existing one-dimensional (1-D) radix-2/4 decimation-in-frequency (DIF) fast Fourier transform (FFT) algorithm is generalized to the case of an arbitrary dimension by introducing a mixture of radix-(2 times 2 times ... times 2) and radix-(4 times 4 times ... times 4) index maps. The introduction of these index maps coupled with an appropriate use of the Kronecker product enable us to design an efficient multi-dimensional (M-D) split vector-radix DIF FFT algorithm and characterize its butterfly by simple closed-form expressions allowing easy software or hardware implementation of the algorithm for any dimension. It is shown that the proposed algorithm substantially reduces the complexity compared to the existing M-D FFT algorithms

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.801
Threshold uncertainty score0.366

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 communication0.0000.001
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 head0.253
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

Quick stats

Citations1
Published2006
Admission routes1
Has abstractyes

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