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Record W1915241179 · doi:10.1109/icassp.2000.861878

Algebraic theory of optimal filter banks

2002· article· en· W1915241179 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 Toronto
Fundersnot available
KeywordsMajorizationMathematicsAlgebraic numberFilter bankFilter (signal processing)Element (criminal law)Coding gainDiscrete mathematicsCoding (social sciences)Mathematical optimizationComputer scienceMathematical analysis

Abstract

fetched live from OpenAlex

We approach the problem of characterizing an optimal FIR filter bank from an algebraic point of view. We introduce the concept of majorization ordering to compare the performance of various filter banks in an admissible set /spl Lscr/. Using the properties of this ordering, we show that a principal component filter bank is associated with the greatest element in /spl Lscr/. A greatest element does not necessarily exist in /spl Lscr/ hence one has to deal with the closely related notion of a maximal element. We show by construction that a maximal element always exist in /spl Lscr/. An interesting result of the presented algebraic theory is that the connection between principal component filter banks and filter banks with maximum coding gain is clearly revealed. In fact, we show that coding gain is a Schur (1973) convex function preserving the order of majorization.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.999

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)0.0010.000

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 head0.045
GPT teacher head0.238
Teacher spread0.193 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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