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Record W1593620144 · doi:10.1109/fpt.2002.1188728

A method of implementing bit-serial LDI ladder filters in FPGAs using JBits

2003· article· en· W1593620144 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 Calgary
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceComputer hardwareLossless compressionFinite impulse responseModelSimReduction (mathematics)Simulated annealingFilter (signal processing)Embedded systemAlgorithmVHDLData compressionMathematics

Abstract

fetched live from OpenAlex

A simulated annealing design method for low hardware cost bit-serial Lossless Discrete Integrator (LDI) recursive digital filter implementations using Field Programmable Gate Arrays (FPGAs) with JBits/spl trade/ is presented. This method jointly minimizes the magnitude frequency response error and the filter hardware cost. The next-neighbor connectivity of bit-serial systems is exploited to create a placement method using JBits/spl trade/ to avoid time-consuming general-purpose placement tools for FPGAs in addition to the hardware cost reduction benefits of bit-serial architectures. A design example using the proposed method is presented in which a 30.2 percent hardware cost reduction is obtained.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.537
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.059
GPT teacher head0.347
Teacher spread0.288 · 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
Published2003
Admission routes1
Has abstractyes

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