Extending the analysis and synthesis approach to classes of nonlinear systems
Bibliographic record
Abstract
This thesis investigates the properties of an analysis and re-synthesis methodof a class of nonlinear systems, with an application to audio effects for guitar. Thegoal of this work is to develop a straightforward method to characterize certaintypes of nonlinear systems (the analysis), and subsequently use this characterizationto create a generic structure for the model of the system. The model imitatesthe nonlinear system's behaviour such that the output of the model to a giveninput signal is the same as the output of the actual nonlinear system under study(the synthesis). A method for system identification of linear systems is first presented,and then the method is extended to analyze nonlinear systems as well.An in-depth presentation of how the method works is presented. The informationextracted by the analysis is then used as parameters in a synthesis modelto emulate a particular nonlinear system under study. The analysis/synthesismethod is then tested on some simple memoryless nonlinear systems with simpleinputs. Finally, three âreal-world' nonlinear systems are then used to validate theanalysis/synthesis method developed in this work. The nonlinear systems areall distortion effects intended for electric guitar. Outputs of the model agreedwell with the actual system output when the input was a simple sinusoid. Themodel's performance did however suffer when a wide-bandwidth musical signal wasused as input. Outputs were lacking in higher harmonic content and overall gain.This is thought to be due to the limited bandwidth of the chirp used as well as alimitation on the number of harmonics that can be modeled.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".