The main challenge in a full-duplex transceiver design is created by the self-interference caused coupling of transmitted signal to transceiver’s own receiver. effect non-linear operation both power amplifier at transmitter and low noise receiver are considered cancelation. performance three cancelers studied: linear cancelation, auto-regressive moving-average (ARMA) based cancelation neural ne...

In this study, the situation of Iran, U.S and Turkey's Pistachio export is investigated. to this purpose, Revealed Comparative Advantage (RCA) Index is calculated based on Agricultural and total economy export, separately, then forecasted by using Auto- Regressive Integrated Moving Average (ARIMA) approached, for 2008-2013. The results show that considering both commodity baskets, Turkey and Ir...

System identification (SI) is the discipline of inferring mathematical models from unknown dynamic systems using input/output observations such with or without prior knowledge some system parameters. Many valid algorithms are available in literature, including Volterra series expansion, Hammerstein–Wiener models, nonlinear auto-regressive moving average model exogenous inputs (NARMAX) and its d...

Air pollution prediction is a burning issue, as pollutants can harm human health. Traditional machine learning models usually aim to improve the overall accuracy but neglect for peak values. Moreover, these are not interpretable. They fail explain interactions between various determining factors and their impacts on air pollution. In this paper, we propose new Hybrid Interpretable Predictive Ma...

With the ever-increasing growth of energy demand and costs, process monitoring operational costs is great importance for industries. In this light, both financial budget management local optimization supposed to be guaranteed properly. To achieve goal, a support vector machine recursive feature elimination (SVM-RFE) method together with clustering algorithm was developed extract features while ...

The article outlines the development of time variable parameter (TVP) estimation as an approach to modeling nonstationary dynamic systems. It then describes one of the latest methods for estimating time variable parameters in dynamic auto-regressive, exogenous variables (DARX) and dynamic transfer function (DTF) models. In the case of DARX models, the estimation methodology is based on standard...