Noise Shaping for Phased Array with Overlapped Sub-Array System
Bibliographic record
Abstract
<p> A novel method is proposed for spectrally shaping the beamforming weights quantization error at the sub-array layer where the in-band distortion intends to move into a position where the sub-array factor has high attenuation. To do that, the sub-array factor or the composite sub-array factor is tiled by the periodicity of the ultimate-layer array factor. Then, the digital filter layout is designed based on the superposition of all tiles intersecting with the visible region of the overall array factor (O-AF), and the O-AF is spectrally shaped to minimize the number of bits quantifying the beamforming weights. The method is investigated for analog, digital, and hybrid array beamforming with multi-layer overlapped sub-array systems of different sizes and shapes. Its performance is promising and potent in alleviating the overall array factor distortion in all cases. </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".