Improved auxiliary particle filter‐based synchronization of chaotic Colpitts circuit and its application to secure communication
Bibliographic record
Abstract
Abstract In this paper, we propose a synchronization scheme based on an improved auxiliary particle filter (IAPF) for chaotic Colpitts circuit and conduct an experimental study on the synchronization performance with application to secure communications. Specifically, with the synchronization scheme, when the chaotic signals generated by an analog Colpitts circuit are transmitted through a nonideal channel, the distorted signals are processed digitally by the novelly designed IAPF at the receiver, in order to obtain the synchronized signals of the transmitter circuit. Experimental results indicate that synchronization can be achieved over both the additive white Gaussian noise channel and the multipath fading channel with low signal‐to‐noise ratio, even if there exist severe circuit parameter mismatches between the transmitter and the receiver. Furthermore, a chaos‐masking secure communication system is constructed and verified over both the additive white Gaussian noise channel and the multipath fading channel, and the bit error rate is evaluated versus different signal‐to‐noise ratios and symbol periods. It is shown that the achievable bit error rate can reach the order of magnitude of 10 − 4 without error correction coding techniques. In addition, security analysis demonstrates that the proposed chaotic secure communication system is resistant to the brute‐force attack. Copyright © 2013 John Wiley & Sons, Ltd.
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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.
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