Abstract:

       One of the most important instruments for prediction of the evolution of stochastic continuous dynamic systems is represented by the Optimal Kalman Filtering (OKF). The intent of this paper is to present how to build OKF architecture and then how to apply a simple, but intuitive algorithm in ten steps by using two theorems. Then we propose an application of OKF for the prediction of the inflation and the expected inflation, by using an anticipative adaptive by learning mechanism.