naa a22 4500 510809634 CHVBK 20180411083436.0 cr unu---uuuuu 180411e20131101xx s 000 0 eng 10.1134/S1064230713060099 doi (NATIONALLICENCE)springer-10.1134/S1064230713060099 Rudenko E. Moscow Aviation Institute, Volokolamskoe sh. 43, 125993, Moscow, Russia aut Optimal structure of continuous nonlinear reduced-order Pugachev filter [Elektronische Daten] [E. Rudenko] A non-parametric synthesis problem is considered for a fast nonlinear low-memory filter consisting of the same number of equations as the number of only information components of the diffusion Markovian state vector of the observation plant. The algorithm for finding mean-square locally optimal structural functions of the filter and the reduced Fokker-Planck-Kolmogorov equation to be used to find the respective instantaneously conditional probability distribution are obtained. The proposed filter in its full order is proved to coincide with the linear Kalman-Bucy filter in various linear Gaussian cases. Ways to construct Gaussian and linearized suboptimal filters are proposed. The example is given where the latter are compared with their analogues. Pleiades Publishing, Ltd., 2013 Journal of Computer and Systems Sciences International Springer US; http://www.springer-ny.com 52/6(2013-11-01), 866-892 1064-2307 52:6<866 2013 52 11488 https://doi.org/10.1134/S1064230713060099 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1134/S1064230713060099 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Rudenko E. Moscow Aviation Institute, Volokolamskoe sh. 43, 125993, Moscow, Russia aut NATIONALLICENCE 773 0- Journal of Computer and Systems Sciences International Springer US; http://www.springer-ny.com 52/6(2013-11-01), 866-892 1064-2307 52:6<866 2013 52 11488 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer