The null-space feasibility test for baseline-estimator constraints determines whether any measurement weights can preserve a specified pulse response while removing the requested backgrounds. Write the conditions as . The criterion in constraint redundancy in baseline-noise minimization is that be orthogonal to every vector in the kernel of .
A singular value decomposition makes this a finite test. Let contain an orthonormal basis for the kernel of and the complementary right singular vectors. ThenThe vector is the component of the required responses outside the attainable response space. No covariance weighting can make an exactly infeasible set of responses feasible.
For an original three-reading example, suppose the sampled signal template is constant: . Requiring unit signal response while rejecting a constant baseline gives and . The kernel basis vector has inner product with , so the conditions are incompatible. A constant signal cannot be distinguished from an unknown constant background by those readings alone.
Projecting onto the attainable space gives . The minimum-norm approximate weights are , giving both signal and baseline response one half. Under independent unit-variance errors their variance is only , but this low value belongs to a different, biased measurement response. It does not solve the requested cancellation problem.
A numerical feasibility residual for baseline constraints needs meaningful scaling of the conditions and a justified singular-value tolerance. Changing time units or allowing a small physical leakage changes the numerical interpretation; it must not silently turn an exact rejection requirement into an approximate one.
NIST's before/after pulse baselines motivate the physical need for a separable pulse and background.[ref]
Calibration Service for Low-level Pulsed-Laser Radiometers at 1.06 µm: Pulse Energy and Peak Power by Rodney W. Leonhardt. §3.5, printed p. 8; §7.2, Leakage Effect
Once feasibility is established, minimum-noise weights under baseline moment constraints uses the actual error covariance to choose among valid estimators. Extra timing information or a different signal template can restore identifiability when the original conditions fail.A response-normalized tolerance for baseline-feasibility residuals measures a pulse estimator's constraint errors against physically chosen response limits. For residual , assign positive tolerances in the corresponding response units and calculateThe criterion means every specified response limit is satisfied. Numerical feasibility residual for baseline constraints explains why a raw unscaled norm alone has no universal physical interpretation.
These tolerances can enforce a deterministic bias budget. If signal and background coefficients are bounded by and , thenThe second inequality follows when the normalized test passes. The allocation of a deterministic bias budget among baseline constraints therefore connects a numerical acceptance criterion to a stated physical error allowance.
For an original example, bound the signal amplitude by , constant background by and drift rate by . Choose signal-response tolerance , constant-response tolerance and linear-time-response tolerance . Their maximum bias contributions are respectively , and , totaling . If all actual residuals are half these tolerances, and the corresponding bias bound is .
The normalized test can be invariant to constraint units. Multiplying one equation and its required response by a nonzero factor multiplies its residual by ; replacing its tolerance by keeps the ratio unchanged. The associated coefficient bound changes inversely, so the physical product is unchanged as well.
NIST's before/after pulse baselines supply a measurement setting where residual offset and drift responses matter.[ref]
Calibration Service for Low-level Pulsed-Laser Radiometers at 1.06 µm: Pulse Energy and Peak Power by Rodney W. Leonhardt. §3.5, printed p. 8; §7.2, Leakage Effect
The example bounds and tolerances are stipulated, not specifications of that apparatus. This deterministic leakage test is separate from noise variance, which needs the actual measurement covariance.[ref]Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results by Barry N. Taylor and Chris E. Kuyatt. Appendix A, equation A-3
Backgrounds outside the assumed family also need separate treatment.