Expand description
Kalman filter (PRML ch 13.3) — exact inference for a linear-Gaussian state-space
model. Recursively estimates the hidden state x and its covariance P from
noisy linear observations. The matrix products reuse linear_algebra::gemm and
the innovation-covariance inverse reuses linear_algebra::cholesky (no new
solver). Kernel-class DenseLinear.
Model: xₜ = F xₜ₋₁ + w (w ~ N(0, Q)), zₜ = H xₜ + v (v ~ N(0, R)).
Predict: x ← Fx, P ← FPFᵀ + Q.
Update with z: S = HPHᵀ + R, K = PHᵀS⁻¹, x ← x + K(z − Hx),
P ← (I − KH)P.
Structs§
- Kalman
Filter - A linear-Gaussian Kalman filter with current state estimate.