WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Kırpılmış ortalamalı gürbüz konum kestiriminde yeni sonuçlar(IEEE, 2014) Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyWhen there are more than necessary distance measurements in localization by distance measurements with closed form estimators, forming smaller subgroups of measurements and averaging the location estimates obtained with these subgroups of measurements makes it possible to eliminate outlier measurements if they are present. In order to eliminate these outlier results, the nearest estimate to the geometric median of estimates is proposed as a reference in this work. Conducted simulation studies show that significant gains can be obtained using geometric median in place of arithmetic average in robust averaging methods.Conference Object Citation - Scopus: 2Nonlinear model selection for PARMA processes using RJMCMC(IEEE, 2017) Karakuş, Oktay; Altınkaya, Mustafa Aziz; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyMany prediction studies using real life measure-ments such as wind speed, power, electricity load and rain-fall utilize linear autoregressive moving average (ARMA) based models due to their simplicity and general character. However, most of the real life applications exhibit nonlinear character and modelling them with linear time series may become problematic. Among nonlinear ARMA models, polynomial ARMA (PARMA) models belong to the class of linear-in-the-parameters. In this paper, we propose a reversible jump Markov chain Monte Carlo (RJMCMC) based complete model estimation method which estimates PARMA models with all their parameters including the nonlinearity degree. The proposed method is unique in the manner of estimating the nonlinearity degree and all other model orders and model coefficients at the same time. Moreover, in this paper, RJMCMC has been examined in an anomalous way by performing transitions between linear and nonlinear model spaces. © EURASIP 2017.