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license: cc-by-4.0
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license: cc-by-4.0
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### Synthetic Signals
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Each signal is \~1M values (1000×1000 or 100×100×100), enabling fair compression analysis.
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| Signal Type | Class Name | Dim | Description |
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| ------------------ | -------------------- | ----- | ---------------------------------------------- |
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| Spheres | `SparseSphereSignal` | 2D/3D | Random circles or spheres with varying scale |
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| Bandlimited | `BandlimitedSignal` | 2D/3D | Low-pass filtered noise with varying frequency |
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| Sierpinski Triangle| `Sierpinski` | 2D | Triangle shaped fractal structure |
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| Star Target | `StarTarget` | 2D | Radial wedges with increasing bandwidth |
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### Real-World Signals
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| Dataset | Class Name | Description |
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| ------------- | --------------- | ------------------------------------------------------------------------------------ |
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| **DIV2K** | `RealImage` | 10 high-res images from DIV2K for image fitting, 4× SR, and denoising |
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| **3D Dragon** | `Voxel_Fitting` | Stanford Dragon. `sparse=True` loads surface version; `False` loads occupancy volume |
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| **CT Scan** | - | 2D human chest CT slice for reconstruction under sparsity |
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