An Accurate Approximation of the Exponential Integral Function Using a Sum of Exponentials
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Bibliographic record
Abstract
This paper proposes a novel approximation for the exponential integral function, E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> [x], using a sum of exponential functions. This approximation facilitates studying the error probability of a number of communication techniques in the presence of Co-Channel Interference (CCI). These include Hybrid Automatic Repeat Request (HARQ) with soft combining, selection relaying, incremental relaying, and opportunistic incremental relaying, just to name a few. To illustrate the usefulness and accuracy of the proposed approximation, we study the error probability of a Chase combining HARQ system operating in the presence of an unknown source of CCI where we derive an accurate closed form expression for the Moment Generating Function (MGF) of the resultant Signal to Interference plus Noise Ratio (SINR). The accuracy of the derived result is verified using computer simulation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 it