Claude
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fcb93ccb2d
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feat: Implement ADR-014 SOTA signal processing (6 algorithms, 83 tests)
Add six research-grade signal processing algorithms to wifi-densepose-signal:
- Conjugate Multiplication: CFO/SFO cancellation via antenna ratio (SpotFi)
- Hampel Filter: Robust median/MAD outlier detection (50% contamination resistant)
- Fresnel Zone Model: Physics-based breathing detection from chest displacement
- CSI Spectrogram: STFT time-frequency generation with 4 window functions
- Subcarrier Selection: Variance-ratio ranking for top-K motion-sensitive subcarriers
- Body Velocity Profile: Domain-independent Doppler velocity mapping (Widar 3.0)
All 313 workspace tests pass, 0 failures. Updated README with new capabilities.
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
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2026-02-28 14:34:16 +00:00 |
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Claude
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6ed69a3d48
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feat: Complete Rust port of WiFi-DensePose with modular crates
Major changes:
- Organized Python v1 implementation into v1/ subdirectory
- Created Rust workspace with 9 modular crates:
- wifi-densepose-core: Core types, traits, errors
- wifi-densepose-signal: CSI processing, phase sanitization, FFT
- wifi-densepose-nn: Neural network inference (ONNX/Candle/tch)
- wifi-densepose-api: Axum-based REST/WebSocket API
- wifi-densepose-db: SQLx database layer
- wifi-densepose-config: Configuration management
- wifi-densepose-hardware: Hardware abstraction
- wifi-densepose-wasm: WebAssembly bindings
- wifi-densepose-cli: Command-line interface
Documentation:
- ADR-001: Workspace structure
- ADR-002: Signal processing library selection
- ADR-003: Neural network inference strategy
- DDD domain model with bounded contexts
Testing:
- 69 tests passing across all crates
- Signal processing: 45 tests
- Neural networks: 21 tests
- Core: 3 doc tests
Performance targets:
- 10x faster CSI processing (~0.5ms vs ~5ms)
- 5x lower memory usage (~100MB vs ~500MB)
- WASM support for browser deployment
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2026-01-13 03:11:16 +00:00 |
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