A real-time systolic array processor implementation of two-dimensional IIR filters for radio-frequency smart antenna applications
Bibliographic record
Abstract
High-speed radio-frequency (RF) applications of 2D HR real-time spatio-temporal digital filters in smart antenna arrays require architectures that are capable of high throughputs. A novel systolic-array architecture is proposed for such filters that operate at a throughput of one-frame-per-clock-cycle (OFPCC). This architecture uses a 2D extension of a well-known ID look-ahead (LA) speed maximization technique to achieve low critical path delays. A method is proposed, simulated, implemented and tested for the broadband beamforming of temporally down-converted RF signals. Temporal down-conversion is used in direct-conversion receivers, implying potential wireless applications. The prototype is operational on a Xilinx 4vsx35ff668-10 FPGA device at a clock frequency of 100 MHz, thereby achieving the required real-time OFPCC frame rate of 100 Million frames/sec. Implementations using high-speed VLSI technologies are envisaged and will facilitate 2D IIR filtering at GHz frame-rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".