A Novel Chaos-Based Transceiver Solution with High Data Rate Capability
Bibliographic record
Abstract
In recent years, chaos-based spread spectrum systems have earned popularity due to the inherent properties of chaos signals; the primary aim of ongoing research being to develop low cost/power solutions with acceptable performance. Although systems proposed to date provide inexpensive solutions, most of the practical implementations fail to support high data-rates. The baseband chaos-based systems implemented to date have offered data-rates in the order of kbps (maximum data-rate -224 kbps). This paper presents a novel design of a chaos-based transceiver architecture with high data-rate capability based on ergodic theory of chaos. The proposed design, coded in VHDL and simulated with Quartus-II is synthesized using Altera Stratix FPGA. Post-synthesis simulation shows that the designed transceiver can be clocked at a maximum frequency of 180.12 MHz, thus, supporting data rates of about 15.01 Mbps. Power consumption of complete transceiver is about 1.284 W, with a power efficiency of 7.704 mW/MS/s.
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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 | 0.000 |
| 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) | 0.002 | 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".