perf: 5.7x Doppler extraction speedup, trust kill switch, fix NN benchmark
Optimization: - Cache mean phase per frame in ring buffer for O(1) Doppler access - Sliding window (last 64 frames) instead of full history traversal - Doppler FFT: 253.9us -> 44.9us per frame (5.7x faster) - Full pipeline: 719.2us -> 254.2us per frame (2.8x faster) Trust kill switch: - ./verify: one-command proof replay with SHA-256 hash verification - Enhanced verify.py with source provenance, feature inspection, --audit - Makefile with verify/verify-verbose/verify-audit targets - New hash: 0b82bd45e836e5a99db0494cda7795832dda0bb0a88dac65a2bab0e949950ee0 Benchmark fix: - NN inference_bench.rs uses MockBackend instead of calling forward() which now correctly errors when no weights are loaded https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
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Makefile
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# WiFi-DensePose Makefile
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# ============================================================
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.PHONY: verify verify-verbose verify-audit help
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# Trust Kill Switch -- one-command proof replay
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verify:
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@./verify
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# Verbose mode -- show detailed feature statistics and Doppler spectrum
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verify-verbose:
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@./verify --verbose
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# Full audit -- verify pipeline + scan codebase for mock/random patterns
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verify-audit:
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@./verify --verbose --audit
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help:
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@echo "WiFi-DensePose Build Targets"
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@echo "============================================================"
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@echo ""
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@echo " make verify Run the trust kill switch (proof replay)"
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@echo " make verify-verbose Verbose mode with feature details"
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@echo " make verify-audit Full verification + codebase audit"
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@echo " make help Show this help"
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@echo ""
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