Open Research Index

Discriminative Kalman Filter Formalized

Michael C. Burkhart

Palomar Registrypalomar/PALOMAR-2026-10-01-000006Oct 1, 2026math.PRscore 0

Asymptotic correctness of the discriminative Kalman filter for a stationary linear Gaussian state model with nonlinear and non-Gaussian observations. Formalizes Appendix B, Theorem 2, Lemma 1, and Remarks 1–4 of Burkhart et al. (2020): weak convergence, eventual Gaussian well-definedness, L1 consistency, the exact Gaussian parameter update, the robust update, and the extension to random input distributions with convergence in probability.

SourceRepositoryJSON

Comments and reviews

No comments yet.

Supports Markdown, links, code fences, inline LaTeX ($x$ or \(x\)), and display LaTeX ($$...$$ or \[...\]).

Drafts stay in this tab.

API

curl /api/v1/records/palomar/PALOMAR-2026-10-01-000006
curl -X POST /api/v1/records/palomar/PALOMAR-2026-10-01-000006/vote -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
  -d '{"value": 1, "emoji": "🤔", "note": "optional"}'
curl -X POST /api/v1/records/palomar/PALOMAR-2026-10-01-000006/comments -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
  -d '{"body": "…", "review": true}'