Bibliographic record
Abstract
A new perturbation technique is proposed which enables adaptive beamforming (ABF) in microwave domain using a single-port beamformer. In this technique, for a system with L antennas, the weight vector is independently perturbed L times to obtain L correlated outputs. These outputs are then used to find a noisy approximation of the antenna array signal for the gradient vector estimation. The process of weight perturbations is performed faster than the Nyquist rate mainly to increase the temporal correlation of the consecutive antenna array signal samples and to lower the perturbation error. Performance of the proposed perturbation technique with the adaptive unconstrained least mean square (ULMS) algorithm is investigated for different channel scenarios. The ULMS algorithm with single-port beamformer converges in very high noise and interference levels and with a convergence speed close to that of the multi-port receiver. After convergence, both the single-port and the multiport beamformer algorithms achieve the same steady state signal to interference plus noise ratio (SINR) gain. Effects of weight quantization are also investigated for the single-port beamformer with the proposed perturbation technique
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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 | 0.001 |
| 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".