Signal design for good correlation for wireless communication, cryptography, and radar
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This book provides a comprehensive, up-to-date description of the methodologies and the application areas, throughout the range of digital communication, in which individual signals and sets of signals with favorable correlation properties play a central role. The necessary mathematical background is presented to explain how these signals are generated, and to show how they satisfy the appropriate correlation constraints. All the known methods to obtain balanced binary sequences with two-valued autocorrelation, many of them only recently discovered, are presented in depth. The authors treat important application areas including: Code Division Multiple Access (CDMA) signals, such as those already in widespread use for cell-phone communication, and planned for universal adoption in the various approaches to 'third-generation'(3G) cell-phone use; systems for coded radar and sonar signals; communication signals to minimize mutual interference ('cross-talk') in multi-user environments; and pseudo-random sequence generation for secure authentication and for stream cipher cryptology
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.
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 | 0.000 |
| 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