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Record W2104322476 · doi:10.1109/tcsi.2008.918214

A Speed-Optimized Systolic Array Processor Architecture for Spatio-Temporal 2-D IIR Broadband Beam Filters

2008· article· en· W2104322476 on OpenAlexaff
Arjuna Madanayake, L.T. Bruton

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2008
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSystolic arrayVery-large-scale integrationGate arrayField-programmable gate arrayComputer scienceInfinite impulse responseBroadbandCritical path methodFrame rateFrame (networking)Filter (signal processing)Latency (audio)Electronic engineeringComputer hardwareElectronic circuitDigital filterEngineeringElectrical engineeringEmbedded systemTelecommunications

Abstract

fetched live from OpenAlex

For high-speed plane-wave filtering applications, real-time 2-D spatio-temporal linear-array broadband beam filters are required, operating at temporal frame rates in excess of hundreds of megahertz. The corresponding application specific VLSI circuits must have low critical-path latencies. A novel high-speed systolic array architecture for a first-order 2-D broadband frequency-planar spatio-temporal beam filter is proposed for this purpose and employs a field-programmable gate array (FPGA) circuit where the critical path latency is minimized by timing optimization of inter- and intra-parallel processor pipelines, together with 3-D look-ahead techniques. The method facilitates single-chip VLSI circuit implementations operating at real-time frame rates of several hundred megahertz.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.031
GPT teacher head0.240
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations49
Published2008
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Circuits and Systems I Regular PapersSame topicDigital Filter Design and ImplementationFrench-language works237,207