How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
A nonzero prearray perturbation changes the posterior but keeps its factor product PSD
Example
Use a scalar state and observation with . The exact measurement prearray is For the perturbation calculation take This is a mathematical backward-perturbation example; it does not assert that a particular floating-point QR produces this exact . The perturbed prearray has the measurement form with and observation coefficient , so the block identity applies to it once its innovation is shown positive below.
Facts & Assumptions
Given: The scalar prearray and the stated nonzero matrix perturbation.
A factor perturbation changes the Gram matrix by at most . A factor perturbation gives an explicit Gram-matrix error
When the innovation block is positive, the lower-right Schur complement of the block QR Gram matrix is represented as . The block QR measurement update gives the canonical Kalman update
Proof
Given: The matrices in the Example.
The exact Gram matrix is Its innovation variance is , its cross covariance is , and its exact posterior covariance is .
The perturbed array and its Gram matrix are Here , , and the Gram difference is , whose Frobenius norm is ; it is bounded by [F1]. The perturbed innovation remains positive, and its Schur complement is This differs from by .
By [F2], the perturbed Schur complement is exactly the represented factor product , so it is positive semidefinite; here it is the positive scalar . The nonzero prearray perturbation changes the posterior covariance, while the factor representation retains positive semidefiniteness.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
8 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.