Differential Code Shifted Reference UWB Receiver Based on Teager-Kaiser Operator
Bibliographic record
Abstract
In order to improve the performance of differential code shifted reference(DCSR)UWB receiver in the presence of narrowband interference(NBI),a new improved DCSR receiver based on Teager-Kaiser operator(TKO)is proposed.By using the nonlinear TKO,the NBI is shifted to a frequency band close to DC,and hence can be removed by a following analog high pass filter.The simulation results show that the proposed receiver can greatly mitigate the narrowband interference(NBI),even in the scenario that no NBI exist the proposed receiver still outperform the original DCSR and TR receiver.Comparing with the original DCSR,the TKO-DCSR receiver achieves significantly performance improvement at the cost of a little increase in complexity,this advantage makes it a promising technology for wireless sensor networks.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".