@article{oai:ir.kagoshima-u.ac.jp:00005916,
 author = {NAKAMORI, Seiichi},
 journal = {鹿児島大学教育学部研究紀要. 自然科学編, Bulletin of the Faculty of Education, Kagoshima University. Natural science},
 month = {2016-10-28},
 note = {This paper newly presents the recursive least-squares (RLS) fixed-lag smoother using the covariance information and then the RLS Wiener fixed-lag smoother in linear discrete-time wide-sense stationary stochastic systems. Here, the additional disturbance in the measurement of the signal is white noise. The signal is uncorrelated with observed noise. It is assumed that the signal process is fitted to the autoregressive (AR) model of order NN. For this AR model of order NN, in the proposed fixed-lag smoother, the fixed-lag smoothing estimate for the fixed lag LL, 1≦LL≦NN−1, can be calculated. The RLS Wiener fixed-lag smoother requires information of the system matrix, the autovariance function of the state vector, the observation vector, the variance of the observation noise and the coefficients for KK(kk−LL, ss) in (19). It is advantageous that the proposed RLS Wiener fixed-lag smoother shows stable and feasible estimation characteristics in comparison with the RLS Wiener fixed-lag smoother [9].},
 pages = {51--66},
 title = {Design of RLS Wiener Fixed-Lag Smoother in Linear Discrete-Time Stochastic Systems},
 volume = {66},
 year = {}
}