A two-stage identification algorithm is introduced for tracking the parameters in time-varying Hammerstein-Wiener systems. The Kalman filtering and parameter separation technique are employed proposed algorithm. convergence analysis of this provided. It shown that can guarantee boundedness estimation error. Four simulation examples, including a practical system application electric arc furnace,...

Financial and economic time series can feature locally explosive behaviour when bubbles are formed. We develop a time-varying parameter model that is capable of describing this in data. Our proposed dynamic be used to predict the emergence, existence burst bubbles. adopt flexible observation driven specification allows for different bubble shapes behaviour. establish stationarity, ergodicity, b...

this paper proposes a new method of gain scheduling control design for a nonlinear system which is described as linear parameter varying form. a performance measure based on linear matrix inequality is introduced. to consider stability and performance measures in design process, the h∞ loop-shaping method is used to design the local controllers, which can be described as state feedback observer...

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. I...

The Kalman filter formula, given by the linear recursive algorithm, is usually used for estimation of the time-varying parameter model. The filtering formula, introduced by Kalman (1960) and Kalman and Bucy (1961), requires the initial state variable. The obtained state estimates are influenced by the initial value when the initial variance is not too large. To avoid the choice of the initial s...