Prediction Methods for Time Series Data with Many Missing Data Based on RLS Method 瀬 戸 要 * ・ 新 井 康 平 *

瀬 戸 要*・ 新 井 康 平* Kaname SETO and Kohei ARAI Abstract : There are two parameter tuning algorithms, time update and measurement update algorithms for parameter estimation of Kalman filter. Two learning methods for parameter estimation of Kalman filter are proposed based on RLS (Recursive Least Square) method. One is the method without measurement update… CONTINUE READING