TY - JOUR ID - 2429 TI - Hidden state estimation in the state space model with first-order autoregressive process noise JO - Iranian Journal of Science JA - ISTT LA - en SN - 2731-8095 AU - Farnoosh, R. AU - Hajrajabi, A. AD - Department of Applied Mathematics, Faculty of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844, Iran AD - Department of Applied Mathematics, Faculty of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844, Iran Y1 - 2014 PY - 2014 VL - 38 IS - 3.1 SP - 321 EP - 327 KW - State space model KW - dependent process noise KW - estimation of the hidden state KW - estimation of the error covariance DO - 10.22099/ijsts.2014.2429 N2 - In this article, the discrete time state space model with first-order autoregressive dependent process noise is considered and the recursive method for filtering, prediction and smoothing of the hidden state from the noisy observation is designed. The explicit solution is obtained for the hidden state estimation problem. Finally, in a simulation study, the performance of the designed method for discrete time state space model with dependent process noise is verified. UR - https://ijsts.shirazu.ac.ir/article_2429.html L1 - https://ijsts.shirazu.ac.ir/article_2429_91e7175ced00a84a7ee6a2c09d9851c0.pdf ER -