Bibliographic record
Abstract
The development of communication systems in the past years has increased the necessity to synthesize very accurate clocks. For example, in Digital Television (DTV) an audio data stream must be inserted into a video data stream, which implies that we must synchronize the audio clock with the video clock. According to one digital audio standard, the audio clock frequency is 5,6448 MHz, and with the PAL digital television standard, the video clock frequency is 35.46895 MHz. In this case, the division ratio is 112896/709379. Other division ratios are required with other DTV standards such as NTSC, SECAM or HDTV, and with other digital audio standard frequencies. Direct Digital Synthesis (DDS) is a popular technique that can be used to derive the audio frequency from the video frequency used as clock. A critical component of a DDS is its phase accumulator, which controls the DDS output frequency. The limited number of bits in the phase accumulator reduces its precision and its ability to express divide ratios defined with large integers. This will produce a phase error that accumulates with time to produce a low-band jitter in the output signal, which is particularly harmful when the output clock is used for synchronization purposes. This paper reviews some circuits found in the literature, which could be used to reduce the phase error given by a phase accumulator, and it presents a new phase correction technique which can give better results in terms of jitter, and which simplify design and implementation of practical DDS circuits.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".