Bibliographic record
Abstract
This paper describes an implementation of a lossless digital waveform coder as a soft-core CPU custom instruction for use in portable electrocardiogram (ECG) recording systems. Holter monitors are portable ECG recorders that are designed to be worn by the patient for a typical period of 24/spl sim/48 hours. Such systems can generate large quantities of data, necessitating some form of coding to reduce the size of the stored data. Traditionally, ECG coding methods employ lossy approaches. While such methods can attain better compression than a lossless method, the reduction in signal fidelity may obscure important details in the signal. The coding algorithm implemented consists of a linear decorrelator selected from analysis of a block of samples, followed by entropy coding of the residual using Golomb-Rice codes. The implementation is designed as a custom instruction for the Altera Nios CPU, and when tested on signals from real ECG libraries, performed approximately seven times faster than a software implementation written in C and running on the same CPU.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".