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Record W1595498052 · doi:10.1109/iscas.2003.1205116

Reducing the computational complexity of narrowband 2D fan filters using shaped 2D window functions

2003· article· en· W1595498052 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
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWindow functionComputational complexity theoryImpulse responseFinite impulse responseNarrowbandMathematicsAlgorithmWedge (geometry)Impulse (physics)Function (biology)Reduction (mathematics)Filter (signal processing)Window (computing)Computer scienceMathematical analysisPhysicsGeometryOptics

Abstract

fetched live from OpenAlex

Two-dimensional (2D) discrete-domain FIR narrow fan filters may be used for the selective filtering of sampled broadband 2D plane waves on the basis of their directions of arrival (DOA). We show that the 2D region of support (ROS) of the unit impulse response h(n/sub 1/,n/sub 2/) of such filters may be reduced in size by using a shaped 2D window function, where the shape is determined by the angle and angular width of the fan. Relative to the widely used square-shaped window function, significant reductions in computational complexity are demonstrated using various shaped window functions. An approximately parabolically-bounded (PB) shaped 2D window function is shown to be especially effective. The method may be extended to 3D cone filters, for which the reduction in computational complexity is expected to be larger than for the 2D case.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.465

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 science0.0000.000
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 head0.064
GPT teacher head0.273
Teacher spread0.208 · 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

Citations21
Published2003
Admission routes1
Has abstractyes

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