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Yayın Automatic modulation classification for mimo systems using fourth-order cumulants(IEEE, 2012) Mühlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jkel, Holger U.; Jondral, Friedrich K.Automatic classification of the modulation type of an unknown communication signal is a challenging task, with applications in both commercial and military contexts, such as spectrum surveillance, cognitive radio, and electronic warfare systems. Most of the automatic modulation classification (AMC) algorithms found in the literature assume that the signal of interest has been transmitted using a single antenna. In this paper, a novel AMC algorithm for multiple input multiple output (MIMO) signals is proposed, which employs fourth-order cumulants as features for classification. First, perfect channel state information (CSI) is assumed. Subsequently, a case of more practical relevance is considered, where the channel matrix is unknown and has to be estimated blindly by employing independent component analysis (ICA). The performance of the proposed classification algorithm is investigated through simulations and compared with an average likelihood ratio test (ALRT) which can be considered as optimum in the Bayesian sense, but has a very high computational complexity.Yayın A novel algorithm for MIMO signal classification using higher-order cumulants(IEEE, 2013) Muehlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jaekel, Holger U.; Jondral, Friedrich K.Automatic modulation classification (AMC) of unknown communications signals is employed in both commercial and military applications, such as cognitive radio, spectrum surveillance, and electronic warfare. Most of the AMC methods proposed in the literature are developed for systems with a single transmit antenna. In this paper, an AMC algorithm for multiple-input multiple-output (MIMO) signals is proposed, which is based on higher-order cumulants. The use of cumulants with different orders, as well as their combinations as feature vectors are investigated. The ideal case of a priori knowledge of the channel state information (CSI) is considered, along with a setting of practical relevance, where the channel matrix is blindly estimated through independent component analysis. The performance of the proposed algorithm with different features is evaluated through simulations and compared with that of the average likelihood ratio test (ALRT).Yayın Cyclostationarity based blind block timing estimation for alamouti coded MIMO signals(IEEE, 2017-06) Gül, Serhat; Öner, Mustafa Mengüç; Çırpan, Hakan AliBlind parameter estimation algorithms provide a powerful tool for application scenarios where the use of training or pilot sequences is not desirable, e.g., in order to improve the bandwidth efficiency of the transmission, or in noncooperative scenarios where such sequences are not available to the receiver. This letter proposes a blind block timing estimation algorithm for Alamouti space-time block coded signals exploiting the second order joint cyclostationary characteristics of the received signal vector, which is induced by the space time block coding operation performed by the transmitter. The proposed algorithm outperforms the existing algorithms by a wide margin.Yayın The comparison of functional connectivity in Parkinson’s Disease patients with and without Parkin gene mutations(Turkish Neuropsychiatric Society, 2025-06-19) Çebi, Merve; Ay, Ulaş; Kıçik, Ani; Erdoğdu, Emel; Tepgeç, Fatih; Uyguner, Zehra Oya; Tüfekçioğlu, Zeynep; Samancı, Bedia; Bilgiç, Başar; Emre, Murat; Demiralp, Tamer; Hanağası, Haşmet AyhanIntroduction: Mapping the functional connectivity of brain regions became appealing in recent research in neurology. Accordingly, a growing body of evidence shows resting-state functional connectivity (rsFC) changes in neurodegenerative disorders including Parkinson’s Disease (PD). As characterised by extensive and progressive dopaminergic loss in the substantia nigra, PD emerges with serious motor and non-motor dysfunctions. In the literature, the minority of PD cases have been associated with certain genetic mutations. The aim of this study was to investigate the rsFC in a group of PD patients having Parkin gene mutation. Method: Twelve PD patients with Parkin mutation (PP-PD), 12 PD patients without Parkin mutation (PN-PD) and 12 healthy controls (HC) were included in the study. All participants underwent a resting-state functional magnetic resonance imaging as well as a neuropsychological assessment and clinical examination. Results: Results indicated that PP-PD had longer disease duration, a higher rate of dyskinesia and lower scores on complex visual perception tests. The resting state networks showed that all PD (consisting of PP-PD and PN-PD) and PP-PD groups had increased functional connectivity in the frontoparietal network as compared to the HC. In addition, the PP-PD group displayed decreased functional connectivity in the dorsal attention network compared to the PN-PD. Conclusion: In conclusion, our data suggests that PD with Parkin gene mutation might be emerging with distinct resting state functional connectivity changes in the brain.
