steady-state gain 0.09512  prior variance P- 0.001051  posterior P 0.000951  (std 0.0308); raw std 0.100
RMSE after sample 100 (mean of 200 runs): raw       0.0997
RMSE after sample 100 (mean of 200 runs): kf        0.0302
RMSE after sample 100 (mean of 200 runs): ema_kinf  0.0302
RMSE after sample 100 (mean of 200 runs): ema_0.5   0.0576
RMSE after sample 100 (mean of 200 runs): ema_0.02  0.0481
gain at samples 1, 2, 5, 10, 50, 399: [0.9901, 0.5, 0.2114, 0.1264, 0.0951, 0.0951]
coverage: fraction of samples after 100 with |error| < 2 sigma_P (200 runs): 0.957
saved /home/user/Documents/DOCUMENTS_SERVER/SKILL_TRAINING/Internet of Things (IoT) and Robotics/sessions/010-unit10-perception/figures/fig03_kalman1d.png
