WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Citation - Scopus: 1Kod Bölüşümlü Çoklu Erişim (cdma) İletişiminde Gauss Olmayan Sönümlü Kanal Kestirimi için Pearson Sistemi'ne Dayalı Gözü Kapalı Kaynak Ayrıştırma Yöntemi(Institute of Electrical and Electronics Engineers Inc., 2004) Kalkan, Olcay; Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this work, a Pearson System based-blind source separation method is used for detecting the signal coming to a mobile user which is subject to multiple access interference in a CDMA downlink communication. Considering some fading channel measurements showing that the fading channel coefficients may have an impulsive nature, these coefficients are modeled with an a-stable distribution whose shape parameter a takes values between 1.8 and 1.9. These a values show that the distribution resembles a Gaussian distribution but has a more impulsive nature. Simulation studies show that the conventional MMSE receiver fails in this impulsive fading scenario. Both the independent component analysis (ICA) method using the conventional hyperbolic tangent score function and the Pearson System-based ICA are successful in estimating the channel coefficients and the proposed Pearson System-based ICA method performs faster.Conference Object Citation - Scopus: 1Özilinti Matrisinin Oluşturulma Yönteminin Modele Dayalı Sinüzoidal Parametre Kestirimindeki Etkileri(Institute of Electrical and Electronics Engineers Inc., 2004) Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyAlthough the maximum likelihood method gives the optimum solutions for the parameter estimation problem of the sinusoids embedded in noise, it is computationally difficult since it generally requires to solve nonlinear optimization problems. So some model-based parameter estimators with high frequency resolution property are preferred quite often. In order to find these estimates the first step is usually forming the autocorrelation (AC) matrix. In this work the effects of the method utilized in the generation of the AC matrix on the performances of sinusoidal parameter estimators are investigated. One way of forming the AC matrix is to use a Toeplitz structure with either the biased or the unbiased AC lag estimates as the matrix elements. Another way is to use the socalled "covariance method" in the AC matrix generation. In this method the matrix formed is no longer Toeplitz; but it is still symmetric. We can think of that the Toeplitz AC matrix is a perturbed version of the non-Toeplitz AC matrix. The differences in the performances of the MUSIC spectral estimator with Toeplitz; and non-Toeplitz AC matrix usage is related to the perturbation in the AC matrix estimate. For this purpose the 3 x 3 AC matrix is is utilized in the estimation of the frequency of a single sinusoid using the MUSIC frequency estimator. The accuracy of the perturbation analysis is checked with the simulation results. Additionally, the fact that the performance of an estimator with data windowing and Toeplitz AC matrix generation becomes near to the performance of the same estimator with non-Toeplitz AC matrix is shown with simulation studies.Conference Object Citation - Scopus: 1Asimetrik Alfa-kararlı Kaynakların Enküçük Saçılım Kriteri Kullalınarak Ayrıştırılması(Institute of Electrical and Electronics Engineers Inc., 2006) Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this work, we extend the method which separates symmetric alpha-stable sources using minimum dispersion criterion to the case of skewed alpha-stable mixtures. Thus, a more robust method based on fractional lower order statistics is developed which is capable of separating general alpha-stable sources.Conference Object Consistency Analysis of Kalman Filter for Modal Analysis of Structures(Institute of Electrical and Electronics Engineers Inc., 2009) Tanyer, İlker; Dönmez, Cemalettin; Özen, Serdar; Özen, Serdar; Dönmez, Cemalettin; Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this paper, Consistency Analysis of Kalman Filter for Modal Analysis of Structural Systems is made. As a future work, A fundamental Modal Analysis algorithm, Eigensystem Realization Algorithm(ERA) will be used with Kalman filters together to make a modal parameter estimation for a structural system. By applying ERA to the impulse response measurements taken from the structure, a state-space representation will be written. Kalman filter will be used as a state estimator in this study and it will have a critical role on minimizing the measurement noise. Before using Kalman filter with ERA, a consistency analysis of Kalman filter is made for artificial impulse response data of the structural system.Conference Object Alpha-Trimmed Means of Multiple Location Estimates(Institute of Electrical and Electronics Engineers Inc., 2013) Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyLocalization by distance measurements is a common technique for solving this contemporary problem. The methods which achieve the theoretically optimum solutions have generally iterative structures. That is why when limited computational load is required, suboptimum methods described by closed form formulas like the one of Coope which depends on orthogonal decomposition of sensor coordinates, are preferred. In this method, when there are more than necessary distance measurements required for localization, the location will be found as the arithmetic average of the estimates obtained using the all three-combinations of distance measurements. In the averaging, eliminating the outlier estimates will increase the performance. In this case discarding the estimates making the ratio of alpha which are farthest away from the arithmetic average, one attains the socalled alpha-trimmed mean of the estimates. Applying this technique, the disturbing effects of impulsive mixture of Gaussian contamination are eliminated and similar performances as in the case of Gaussian distance measurements are attained in localization.Conference Object The Effect of Convolutional Encoder Memory on the Sphere Decoding Search Radius in Mimo Systems(Institute of Electrical and Electronics Engineers Inc., 2013) Karakuş, Oktay; Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; Kılıçaslan, Kağan; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn the new generation communication systems Multiple-Input-Multiple-Output systems are frequently used. The processing load of the Maximum Likelihood (ML) Detector which is the optimum detector for these systems, increases exponentially as a function of system dimension and memory due to testing all possible points. Sphere Decoding (SD) method which tests only the probable points, decreases the processing load dramatically. System memory changes by system dimensions and length of the convolutional encoder. This, in turn, affects the radius of the hyper sphere centered at the observation in the observation space at which SD attains the performance of the ML detector. This effect is investigated via simulation studies. In these simulations, it is observed that the radius of the SD is relatively smaller than the one in ML, and the ratio between the radius values varies from 6,61 in the case of memoryless 2x2 MIMO system to 1,02 in the case of 8x8 MIMO system with memory K=10 according to increased antenna numbers and system memory. In addition to these, it is observed that the radius of the hyper sphere is directly proportional to the memory of the encoder.Conference Object A Bayesian Approach for Licence Plate Recognition Developed on a Realistic Simulation Environment(Institute of Electrical and Electronics Engineers Inc., 2013) Efeler, Mahmut Cenk; Efeler, Mahmut Cenk; Altınkaya, Mustafa Aziz; Gümüştekin, Şevket; Gümüştekin, Şevket; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyTemplate matching is one of the most common methods for license plate recognition. This method discards prior probabilities of license plate codes. The posterior code class probabilities constructed by including the prior probability information are expected to improve the recognition performance. The probability information that needs to be included requires extensive training data, which is quite costly to obtain. In order to generate these training images a license plate image simulator is developed with a realistic noise model. Simulated license plate images are then used to test a Bayesian decision theory based recognition procedure. Test results indicate that, with the inclusion of prior information, significant recognition gain is obtained with respect to standard template matching method at high noise levels.Conference Object Citation - WoS: 5Estimation of the Nonlinearity Degree for Polynomial Autoregressive Processes With Rjmcmc(Institute of Electrical and Electronics Engineers Inc., 2015) Karakuş, Oktay; Altınkaya, Mustafa Aziz; Kuruoğlu, Ercan E.; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyDespite the popularity of linear process models in signal and image processing, various real life phenomena exhibit nonlinear characteristics. Compromising between the realistic and computationally heavy nonlinear models and the simplicity of linear estimation methods, linear in the parameters nonlinear models such as polynomial autoregressive (PAR) models have been accessible analytical tools for modelling such phenomena. In this work, we aim to demonstrate the potentials of Reversible Jump Markov Chain Monte Carlo (RSMCMC) which is a successful statistical tool in model dimension estimation in nonlinear process identification. We explore the capability of RJMCMC in jumping not only between spaces with different dimensions, but also between different classes of models. In particular, we demonstrate the success of RJMCMC in sampling in linear and nonlinear spaces of varying dimensions for the estimation of PAR processes.Conference Object Citation - WoS: 2Citation - Scopus: 3Long Term Wind Speed Prediction With Polynomial Autoregressive Model(Institute of Electrical and Electronics Engineers Inc., 2015) Karakuş, Oktay; Altınkaya, Mustafa Aziz; Kuruoğlu, Ercan E.; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyWind energy is one of the preferred energy generation methods because wind is an important renewable energy source. Prediction of wind speed in a time period, is important due to the one-to-one relationship between wind speed and wind power. Due to the nonlinear character of the wind speed data, nonlinear methods are known to produce better results compared to linear time series methods like Autoregressive (AR), Autoregressive Moving Average (ARMA) in predicting in a period longer than 12 hours. A method is proposed to apply a 48-hour ahead wind speed prediction by using the past wind speed measurements of the (Cesme Peninsula. We proposed to model wind speed data with a Polynomial AR (PAR) model. Coefficients of the models are estimated via linear Least Squares (LS) method and up to 48 hours ahead wind speed prediction is calculated for different models. In conclusion, a better performance is observed for higher than 12-hour ahead wind speed predictions of wind speed data which is modelled with PAR model, than AR and ARMA models.Conference Object Citation - Scopus: 1Optimal Quantization in Decentralized Detection by Maximizing the Average Entropy of the Sensors(Institute of Electrical and Electronics Engineers Inc., 2019) Wahdan, Muath A.; Altınkaya, Mustafa Aziz; Altınkaya, Mustafa Aziz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn a wireless sensor network the sensor outputs are required to be quantized because of energy and bandwidth requirements. We propose such a distributed detection scheme for a point source which is based on Neyman-Pearson criterion where sensor outputs are quantized maximizing the average output entropy of the sensors under both hypotheses. The quantized local outputs are transmitted to a fusion center (FC) where they are used to make a global decision. The performance of the proposed maximum average entropy (MAE) method in quantizing sensor outputs was tested for binary, ternary and quarternary quantization. The effects of the channel from the sensors to the FC is also addressed by simplified channel models. The simulation studies show the success of the MAE method.