Assuming an auto regressive (AR) lter model driven by a non-Gaussian white noise we formulate a general parameter estimation problem. A maximum likelihood solution gives an AR estimate of the l-ter and the probability distribution function parameters for non-Gaussian input. The proposed method is optimal in the information theoretic sense, giving the most probable model for the source and lter ...

Model predictive control (MPC) is used in the CO2 removal process Subang field to improve its performance. MPC maintain concentration at sweet gas output by controlling feed pressure (PIC-1101), makeup water flow rate (FIC-1102), and amine (FIC-1103). The empirical model applied represent auto-regressive exogenous (ARX) model. ARX compared with first order plus dead time (FOPDT) based on root m...

The field of Operational Modal Analysis (OMA) has recently become an emerging research interest. OMA, also known as Response-Only Modal Analysis, extracts the modal parameters by processing only the system response data. In many experimental measurement situations, the system’s output data series is short in length and buried under potentially correlated noise. In such cases, the separation of ...

raisin is the second major export item in iranian agricultural section after pistachio. in this study, effects of exchange rate fluctuations were investigated on quantity and price of exported raisin. therefore, data of 1970 to 2008 were reviewed by time series analysis and estimated by auto-regressive distributed lag model (ardl). results show the absence of a long-term relationship between ex...

In this paper, we propose a time series based method for analyzing and predicting personal medical data. First, we introduce an auto-regressive integrated moving average model which is good for all time series processes. Second, we describe how to identify a personalized time series model based on the patient’s history information, followed by estimating the parameters in the model. Furthermore...

Parametric identification approaches in the Linear Parameter-Varying (LPV) setting require optimal prior selection of a set of functional dependencies, used in the parametrization of the model coefficients, to provide accurate model estimates of the underlying system. Consequently, data-driven estimation of these functional dependencies has a paramount importance, especially when very limited a...

Spam has been one of the most difficult problems to be addressed since the invention of Internet. Outbound spam can reflect the information security level of an organization as most spam emails are generated by compromised computers. Understanding the trend of outbound spam can help organizations adopt proactive policies and measures toward a more informed decision on resource allocation in ter...