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 ...

background: with increasing age, some changes appeared in specifications of vessels which including dimensions and elasticity in their. the changes in parameters such as resistance, inertance and compliance vessels appear and eventually changes in the environmental pulse releases are in circulation. these changes clearly appear in specification of photoplethysmogram particularly in the size and...

The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is...

the stability analysis of islanded inverter-based microgrids (ibmgs) is increasingly an important and challenging topic due to the nonlinearity of ibmgs. in this paper, a new linear model for such microgrids as well as an iterative method to correct the linear model is proposed. using the linear model makes it easy to analyze the eigenvalues and stability of ibmgs due to the fact that it derive...

neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...