Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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End date: 2009Institution Author: search.filters.institutionAuthor.Altınkaya, Mustafa Aziz

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Now showing 1 - 8 of 8
  • Research Project
    Bağımsız bileşen analizinin iletişim, imge işleme ve jeofizikteki uygulamaları
    (TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2006) Sankur, Bülent; Gençağa, Deniz; Kalkan, Olcay; Altınkaya, Mustafa Aziz
    Bu projede literatürde kaynak ayrıştırma olarak bilinen istatistiksel işaret işleme yöntemleri hem kuramsal açıdan, hem de uygulamaları açısından ele alınmıştır. Kuramsal çalışmalarda, kaynakların uzamda ve zamanda birbirlerinden bağımsız olmadıkları düşüncesiyle parçacık süzgeçleri yöntemi ele alınmıştır. Bu yaklaşımda süreç hakkında elimizde varolan önsel bilgilerin algoritmaya ağdırılması mümkün olmuştur. Ayrıca durağan olmayan süreçlerin de ayrıştırılma problemi ele alınmış, farklı yeniden örnekleme ve önem fonksiyonları seçerek literatürdeki teknikleri aşan sonuçlar bulunmuştur. Uygulamaya dönük çalışmalarda ise, jeofizik işaret işlemede klimatolojik verilere bakılmış ve gerek Kuzey Atlantik Salınımı diye adlandırılan olgu irdelenmiştir. Ancak topografık etkiler istenen sonuca ulaşılmasına engel olmuştur. Öte yandan sıcaklık verileri faktör analizi ile incelenmiş ve volkanik hareketlerin etkisi ortaya çıkarılmaya çalışılmıştır. Beyin-işaretleri konusunda özellikle prefrontal korteks bölgesinden bilişsel süreçlerle ilgili araştırmalar yapılmıştır. Deneklerin biliş esnasında beyindeki kan dengesinin, oksi- ve deoksi hemoglobinin değişimleri yakalanmaya çalışılmıştır. Bağımsız bileşen analizinin bu türlü dalga biçimlerini ortaya çıkarmakta çok etkili bir araç olduğu gösterilmiştir. Biyometri alanında, bağımsız bileşenler analizi hem yüz imgelerine hem de el imgelerine uygulanmıştır. Bağımsız-bileşenlerin deneklerin kimlik bilgilerini taşıyan ve bozucu etkilere karşı en dayanıklı öznitelikler olduğu görülmüştür. Nihayet bağımsız bileşen analizi CDMA: kod bölüşümlü çoklu erişim işaretlerine uygulanmış ve sönümlü kanallardaki alıcının performansını iyileştirici tasarımlar irdelenmiştir.
  • Conference Object
    Citation - Scopus: 1
    Kod 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
    In 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: 1
    Özilinti Matrisinin Oluşturulma Yönteminin Modele Dayalı Sinüzoidal Parametre Kestirimindeki Etkileri
    (Institute of Electrical and Electronics Engineers Inc., 2004) Altınkaya, Mustafa Aziz
    Although 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: 1
    Asimetrik Alfa-kararlı Kaynakların Enküçük Saçılım Kriteri Kullalınarak Ayrıştırılması
    (Institute of Electrical and Electronics Engineers Inc., 2006) Altınkaya, Mustafa Aziz
    In 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.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Phase Dependence Mitigation for Autocorrelation-Based Frequency Estimation
    (Elsevier Ltd., 2008) Altınkaya, Mustafa Aziz; Anarım, Emin; Sankur, Bülent
    The sinusoidal frequency estimation from short data records based on Toeplitz autocorrelation (AC) matrix estimates suffer from the dependence on the initial phases of the sinusoid(s). This effect becomes prominent when the impact of additive noise vanishes, that is at high signal-to-noise ratios (SNR). Based on both analytic derivation of the AC lag terms and simulation experiments we show that data windowing can mitigate the limitations caused by the phase dependence. Thus with proper windowing, the variance of the frequency estimate is no more eclipsed by phase dependence, but it continues to decrease linearly with increasing SNR. The study covers both the cases of a single sinusoid and two sinusoids closely spaced in the frequency with the Pisarenko frequency estimator, MUSIC and principal component autoregressive frequency estimators. The trade-offs between the spectral broadening and the achieved minimum variance level due to the data window are analyzed in detail.
  • Conference Object
    Phase Noise Mitigation in the Autocorrelation Estimates With Data Windowing: the Case of Two Close Sinusoids
    (Institute of Electrical and Electronics Engineers Inc., 2006) Altınkaya, Mustafa Aziz; Anarım, Emin; Sankur, Bülent
    We address the phase noise and the superresolution problem in Toeplitz matrix-based spectral estimates. The Toeplitz autocorrelation (AC) matrix approach in spectral estimation brings in an order of magnitude computational advantage while the price paid is the phase noise that becomes effective at high signal-to-noise ratios (SNR). This noise can be mitigated with windowing the data though some concomitant loss in resolution occurs. The trade-offs between additive noise SNR, resolvability of sinusoids closer than the resolution limit, and behavior of the estimated AC lags and tone frequencies are investigated.
  • Conference Object
    Citation - Scopus: 1
    Removal of the Phase Noise in the Autocorrelation Estimates With Data Windowing
    (Institute of Electrical and Electronics Engineers Inc., 2005) Altınkaya, Mustafa Aziz; Anarım, Emin; Sankur, Bülent
    The sinusoidal frequency estimation from short data records based on Toeplitz autocorrelation (AC) matrix estimates suffer from phase noise. This effect becomes prominent especially when additive noise vanishes becoming a nuisance, that is at high signal-to-noise ratios (SNR). Based on both analytic derivation of the AC lag terms and simulation experiments, we show that data windowing can mitigate the limitations caused by the phase noise. Thus with proper windowing, the variance of the frequency estimate is no more limited by phase noise, but it continues to decrease linearly with the SNR. The cases of the Pisarenko frequency estimator and of MUSIC, both for the single sinusoid case, are analyzed in detail.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 15
    Subspace-Based Frequency Estimation of Sinusoidal Signals in Alpha-Stable Noise
    (Elsevier Ltd., 2002) Altınkaya, Mustafa Aziz; Deliç, Hakan; Sankur, Bülent; Anarım, Emin
    In the frequency estimation of sinusoidal signals observed in impulsive noise environments, techniques based on Gaussian noise assumption are unsuccessful. One possible way to find better estimates is to model the noise as an alpha-stable process and to use the fractional lower order statistics (FLOS) of the data to estimate the signal parameters. In this work, we propose a FLOS-based statistical average, the generalized covariation coefficient (GCC). The GCCs of multiple sinusoids for unity moment order in SαS noise attain the same form as the covariance expressions of multiple sinusoids in white Gaussian noise. The subspace-based frequency estimators FLOS-multiple signal classification (MUSIC) and FLOS-Bartlett are applied to the GCC matrix of the data. On the other hand, we show that the multiple sinusoids in SαS noise can also be modeled as a stable autoregressive moving average process approximated by a higher order stable autoregressive (AR) process. Using the GCCs of the data, we obtain FLOS versions of Tufts-Kumaresan (TK) and minimum norm (MN) estimators, which are based on the AR model. The simulation results show that techniques employing lower order statistics are superior to their second-order statistics (SOS)-based counterparts, especially when the noise exhibits a strong impulsive attitude. Among the estimators, FLOS-MUSIC shows a robust performance. It behaves comparably to MUSIC in non-impulsive noise environments, and both in impulsive and non-impulsive high-resolution scenarios. Furthermore, it offers a significant advantage at relatively high levels of impulsive noise contamination for distantly located sinusoidal frequencies.