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Cited by 39 publications
(28 citation statements)
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References 63 publications
(63 reference statements)
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“…We will also replace the MLP with other fusion methods to reduce the network model’s parameters for the fusion results. The proposed approaches in the paper can combine other parameter estimation algorithms [ 32 , 64 , 65 , 66 , 67 ] to study the parameter identification problems of linear and nonlinear systems with different disturbances [ 68 , 69 , 70 , 71 , 72 ], and to build the soft sensor models and prediction models and can be applied to other fields [ 73 , 74 , 75 , 76 , 77 ] such as signal processing and process control systems.…”
Section: Discussionmentioning
confidence: 99%
“…We will also replace the MLP with other fusion methods to reduce the network model’s parameters for the fusion results. The proposed approaches in the paper can combine other parameter estimation algorithms [ 32 , 64 , 65 , 66 , 67 ] to study the parameter identification problems of linear and nonlinear systems with different disturbances [ 68 , 69 , 70 , 71 , 72 ], and to build the soft sensor models and prediction models and can be applied to other fields [ 73 , 74 , 75 , 76 , 77 ] such as signal processing and process control systems.…”
Section: Discussionmentioning
confidence: 99%
“…The simultaneous update of the state and model parameters may also make the system parameter optimization process unable to converge. These methods can combine identification approaches [ 71 , 72 , 73 , 74 , 75 ] for studying the modeling of dynamic time series and stochastic systems with colored noises [ 76 , 77 , 78 , 79 , 80 ] and can be applied to other fields such as signal modeling, tracking and control systems [ 81 , 82 , 83 ].…”
Section: State Estimation Based On a Blurry Modelmentioning
confidence: 99%
“…3) Compute the gain vector L s (t) and the covariance matrix P s (t) by (45) and (46). Compute the gain vector L n (t) and the covariance matrix P n (t) by (47) and (48). 4) Update the parameter estimatesθ s (t) andθ n (t) by (43) and (44), respectively.…”
Section: Algorithmmentioning
confidence: 99%