RT Journal Article ID 19cc197e4c3d3685 A1 Skorohod, Boris A. T1 Diffuse Initialization of Kalman Filter JF Journal of Automation and Information Sciences JO JAI(S) YR 2011 FD 2011-05-01 VO 43 IS 4 SP 20 OP 34 K1 Kalman filter K1 random variables K1 covariance matrix K1 estimation algorithm K1 separable regression AB The behavior of Kalman filter is studied at interpretation of unknown initial conditions as the random variables having a covariance matrix proportional to large positive parameter. The developed approach allows one to express characteristics of the filter in an analytic form, to explain a phenomenon of divergence and propose a limiting estimation algorithm which is independent of large initial parameter leading to divergence. As the application there were considered two problems: filtering with a sliding window and a parameter estimation of separable regression. The received results are illustrated by example of training a radial basic neural network. PB Begell House LK https://www.dl.begellhouse.com/journals/2b6239406278e43e,7312ef6706f9b132,19cc197e4c3d3685.html