18170d7daf
All ADR-017 integration points now implemented: --- wifi-densepose-signal --- 1. subcarrier_selection.rs — ruvector-mincut: mincut_subcarrier_partition uses DynamicMinCut to dynamically partition sensitive/insensitive subcarriers via O(n^1.5 log n) graph bisection. Tests: 8 passed. 2. spectrogram.rs — ruvector-attn-mincut: gate_spectrogram applies self-attention (Q=K=V, configurable lambda) over STFT time frames to suppress noise/multipath interference. Tests: 2 added. 3. bvp.rs — ruvector-attention: attention_weighted_bvp uses ScaledDotProductAttention for sensitivity-weighted BVP aggregation across subcarriers (vs uniform sum). Tests: 2 added. 4. fresnel.rs — ruvector-solver: solve_fresnel_geometry estimates unknown TX-body-RX geometry from multi-subcarrier Fresnel observations via NeumannSolver. Regularization scaled to inv_w_sq_sum * 0.5 for guaranteed convergence (spectral radius = 0.667). Tests: 10 passed. --- wifi-densepose-mat --- 5. localization/triangulation.rs — ruvector-solver: solve_tdoa_triangulation solves multi-AP TDoA positioning via 2×2 NeumannSolver normal equations (Cramer's rule fallback). O(1) in AP count. Tests: 2 added. 6. detection/breathing.rs — ruvector-temporal-tensor: CompressedBreathingBuffer uses TemporalTensorCompressor with tiered quantization for 50-75% CSI amplitude memory reduction (13.4→3.4-6.7 MB/zone). Tests: 2 added. 7. detection/heartbeat.rs — ruvector-temporal-tensor: CompressedHeartbeatSpectrogram stores per-bin TemporalTensorCompressor for micro-Doppler spectrograms with hot/warm/cold tiers. Tests: 1 added. Cargo.toml: ruvector deps optional in MAT crate (feature = "ruvector"), enabled by default. Prevents --no-default-features regressions. Pre-existing MAT --no-default-features failures are unrelated (api/dto.rs serde gating, pre-existed before this PR). Test summary: 144 MAT lib tests + 91 signal tests = all passed. cargo check wifi-densepose-mat (default features): 0 errors. cargo check wifi-densepose-signal: 0 errors. https://claude.ai/code/session_01BSBAQJ34SLkiJy4A8SoiL4
135 lines
3.3 KiB
JSON
135 lines
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JSON
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