MétaCan
Menu
Back to cohort
Record W2157657466 · doi:10.1109/iscas.1997.609011

A least-square method for the design of 2-D FIR digital filters with arbitrary frequency responses

2002· article· en· W2157657466 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
KeywordsFinite impulse responseDigital filterLinear phaseFrequency responseFilter designLinear filterSquare (algebra)Computer sciencePrototype filterControl theory (sociology)Impulse responseAlgorithmMathematicsLow-pass filterNetwork synthesis filtersFilter (signal processing)Electronic engineeringMathematical analysisEngineering

Abstract

fetched live from OpenAlex

In this paper, the least-square design problem of 2-D FIR digital filters with arbitrary frequency responses is investigated. By exposing and exploiting some of the characteristics of the complex matrices associated with the approximation problem, a closed-form solution is developed. The solution is presented as an explicit expression for the impulse response corresponding to the desired frequency response specifications. Thus, the method avoids the usual time-consuming procedures of optimization or matrix inversion and makes an extremely fast calculation of the filter's coefficients possible. It is also shown that when this solution is used to design some specific classes of filters, further computational savings can be achieved. Design examples for both linear-phase and nonlinear-phase filters are considered.

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 score0.855
Threshold uncertainty score0.291

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 science0.0010.000
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 head0.081
GPT teacher head0.289
Teacher spread0.209 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicDigital Filter Design and ImplementationFrench-language works237,207