Overview
Explore how signals are detected in noise using filtering and matched detection techniques.
This interactive tool allows you to explore signal detection simulator through hands-on calculation and visualization.
How It Works
Simulator Mode
Set initial conditions and run the simulation to see how the system evolves according to SCU dynamics.
Inputs
| Signal Type | Waveform shape | sine | |
|---|---|---|---|
| Signal Amplitude | Signal strength | 1.0 | |
| Noise Level | Noise standard deviation | 0.5 |
Outputs
- SNR: Signal-to-noise ratio
- Detection Probability: Likelihood of detection
The Mathematics
The tool implements these core SCU equations:
Master Equation M1 (Geometry):
G_{\mu\nu} = 8\pi G T_{\mu\nu}[\alpha]
Master Equation M2 (Flow):
\nabla_\mu(\alpha^4 u^\mu) = 0
Master Equation M3 (Balance):
\nabla_\mu T^{\mu\nu} = 0
Try It
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Understanding the Results
The outputs reveal how α-field dynamics govern this phenomenon:
- Scale dependence - How behavior changes across scales
- Regime transitions - Moving between laminar, turbulent, and resonant states
- Emergent properties - What arises from the underlying dynamics
Related Tools
- what-is-signal-detection
- what-is-signal-to-noise-ratio
Learn More
Connect this tool to the underlying theory:
- Understand the equations being computed
- See how this relates to observable phenomena
- Explore the evidence supporting these predictions