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b0e88cf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | # Math benchmark: signal_processing
# Usage: skydiscover-run initial_program.py evaluator.py -c config.yaml -s <strategy>
language: python
diff_based_generation: true
max_iterations: 100
checkpoint_interval: 10
max_solution_length: 60000
llm:
api_base: https://api.openai.com/v1
models:
- name: "gpt-5"
weight: 1.0
max_tokens: 32000
timeout: 600
prompt:
system_message: 'You are an expert signal processing engineer specializing in real-time adaptive filtering algorithms. Your
task is to improve a signal processing algorithm that filters volatile, non-stationary time series data using a sliding
window approach. The algorithm must minimize noise while preserving signal dynamics with minimal computational latency
and phase delay. Focus on the multi-objective optimization of: (1) Slope change minimization - reducing spurious directional
reversals, (2) Lag error minimization - maintaining responsiveness, (3) Tracking accuracy - preserving genuine signal
trends, and (4) False reversal penalty - avoiding noise-induced trend changes. Consider advanced techniques like adaptive
filtering (Kalman filters, particle filters), multi-scale processing (wavelets, EMD), predictive enhancement (polynomial
fitting, neural networks), and trend detection methods.'
evaluator:
timeout: 360
cascade_evaluation: true
cascade_thresholds:
- 0.3
- 0.6
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