state-space model
A canonical space-time state space model: state and parameter estimation
... joint state and parameter estimation problem for the general, linear state-space ...spatio–temporal model outlined earlier, the construction of the likelihood for the EM algorithm’s M-step ...
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Online State Space Model Parameter Estimation in Synchronous Machines
... nonlinear model of synchronous generators is ...nonlinear state space ...nonlinear state space model is converted to only two linear regression ...
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State Space Model Predictive Control of an Aerothermic Process with Actuators Constraints
... investigates State Space Model Predictive Control (SSMPC) of an aerothermic ...multi-variable state space model is ob- tained from on-line experimental ...
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Bayesian Prediction of Bi Component State Space Model to Chinese Population
... Figure 8 shows that Chinese migration data is not accurate and stable enough so the number of net migration in each age-gender-time group is obtained indirectly from population and mortality rate data. The net migration ...
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A Learning State-Space Model for Image Retrieval
... a state-space model for learning the user concepts in image ...a state-space model for interactive image retrieval, including likelihood and transition models, and we also ...
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Estimation of bubble dynamics in the Chinese real estate market: a state space model
... a state space model to examine the existence of a real estate bubble in ...a state space model. The state space model has been increasingly used in recent ...
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Estimation of Unobserved Inflation Expectations in India using State Space Model
... This paper estimates the unobserved quarterly in‡ation expectations in India between 1993:Q1 and 2016:Q1 from the Fisher equation by using the state-space model. Our estimates match well with the ...
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A Flexible State Space Model and its Applications
... standard state space model (SSM) treats observations as imprecise mea- sures of the Markov latent ...ARMA model, mixed frequency regression and the dynamic factor model with missing ...
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Forecasting macroeconomic variables using a structural state space model
... In particular, the first objective was achieved (in part) by showing how the charac- ter of a SVAR specification may be incorporated into a structural state space model. Furthermore, long run (inter) ...
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RESULTS OF INTERBANK EXCHANGE RATES FORECASTING USING STATE SPACE MODEL
... and state space approach have been described and compared for forecasting the interbank exchange ...important model considered here is the state space ...the state space ...
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Reliability state space model of Power Transformer
... The state space model of core, tank ,oil, cooler, bushing and dielectric material is two state because two state available up and down and failure rate of core , tank ,bushing , cooler, ...
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Filtering and identification of a state space model with linear and bilinear interactions between the states
... bilinear state space model and describe a generalization of the Kalman filter and smoother to this ...Our model subsumes the well-known Lorentz- model [] for weather forecast, and the ...
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A new stochastic and state space model of human colon cancer incorporating multiple pathways
... a state space model for human colon cancer. In this state space model, the stochastic system is represented by a stochastic model, involving 2 different pathways-the ...
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Estimation of Unobserved Inflation Expectations in India Using State Space Model
... DOI: 10.4236/tel.2019.95095 1485 Theoretical Economics Letters model. Our estimates match well with the inflation forecasts made by the SPF and IESH conducted by the RBI and the inflation forecasts of India made ...
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Development of a kinematic GNSS Acoustic positioning method based on a state space model
... observation model, parameters expressing underwater sound speed struc- ture [nadir total delay (NTD) and underwater delay gradients] are defined in a similar manner to the satellite geodetic ...
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Linear Switching State Space (LS3) Model for Task Scheduling: An Analytical Approach
... switching state space model opens a possibility of using the extensive theoretical developments that have taken place in this field within the past several ...nonlinear state space ...
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Market Risk Beta Estimation using Adaptive Kalman Filter
... Literature shows that there have been quite a number of techniques for beta estimation: OLS [5, 4, 15], GLS [27], KF [6, 12, 4, 26, 14], Adaptive KF [28]. [27] compared GLS and KF for purpose of estimation of ...
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Dynamic State Space Models
... dynamic state-space model was developed in the control systems literature, where physi- cal systems are described mathematically as sets of inputs, outputs, and state variables, related by ...
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Pricing of Commodity Futures Contract by Using of Spot Price Jump-Diffusion Process
... no-jump model has a normal distribution and the Kalman filter algorithm can be used to filter the state variable vector and to estimate its ...linear state space model with normal ...
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Modeling And Control Of A Car Suspension System Using P, Pi, Pid, Ga-pid And Auto-tuned Pid Controller In Matlab/simulink
... ¼ model of car suspension system using transfer function and state space model in ...open-loop state space response that for a unit step high actuated force; the system is ...
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