Notes · · Nonstationary plants

Adaptive x* for permanent regime shifts

Workbench probe v5 + realdata v6. Not “no configuration required.”

With a frozen normal, GSRF will not fully adopt a permanent level change— that is peak-compression identity. Production plants still change operating points. The fix is not to lie about the spring; it is to move the thermostat slowly.

Synthetic probe (50 → 70 → 40)

Mean absolute mean-error vs true regime base on the shifted regimes (B+C):

In the original regime, adaptive GSRF still beat EMA on oscillation (osc31 ~0.50 vs ~0.78 in that probe).

Real-data nuance

On the realdata v6 matrix, adaptive often keeps phase5/phase6.2 osc wins and can help multi-regime MBP-style traces. It can hurt flat SpO2-like series—do not enable adaptive blindly on clipped nearly-constant signals.

Implementation sketch

Causal adaptive x*: trailing median of log(signal) over a window, updated online while the same GSRF Practical state continues. That is what the workbench probe used—not a second filter fighting the first.

Sources: Evidence §3 · probes v5 adaptive · realdata v6. /evidence#adaptive

Questions people actually ask

When should I use adaptive x*?

When the operating point permanently moves (regime jumps). Frozen x* sticks near the old normal; adaptive trailing median reduced mean regime error in locked probes.

Can adaptive x* hurt?

Yes — adaptive can hurt flat SpO2-like traces. Document the policy; do not blindly adapt everything.

Does adaptive remove the spring?

No. Adaptive moves the setpoint x*; k_return still springs toward the current normal.

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