SCI: An Equilibrium for Signal Intelligence
- URL: http://arxiv.org/abs/2511.12240v1
- Date: Sat, 15 Nov 2025 14:48:17 GMT
- Title: SCI: An Equilibrium for Signal Intelligence
- Abstract summary: We present SCI, a control-theoretic framework that models interpretability as a regulated state.<n> SCI formalizes the interpretive error Delta SP and actively drives SP(t) in [0, 1] toward a target via a projected update on the parameters Theta under a human-gain budget.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present SCI, a closed-loop, control-theoretic framework that models interpretability as a regulated state. SCI formalizes the interpretive error Delta SP and actively drives SP(t) in [0, 1] ("Surgical Precision") toward a target via a projected update on the parameters Theta under a human-gain budget. The framework operates through three coordinated components: (1) reliability-weighted, multiscale features P(t, s); (2) a knowledge-guided interpreter psi_Theta that emits traceable markers and rationales; and (3) a Lyapunov-guided controller equipped with rollback, trust-region safeguards, and a descent condition. Across biomedical (EEG/ECG/ICU), industrial (bearings/tool wear), and environmental (climate/seismic) domains, SCI reduces interpretive error by 25-42% (mean 38%, 95% confidence interval 22-43%) relative to static explainers while maintaining AUC/F1 within approximately 1-2 percentage points of baseline. SCI also reduces SP variance from 0.030 to 0.011, indicating substantially more stable explanations. Modeling interpretability as a control objective yields steadier, faster-recovering, and more trustworthy interpretive behavior across diverse signal regimes.
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