Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Citation - Scopus: 2Enhancing Multiview 3d Reconstruction Using Polarization Imaging(IEEE Computer Society, 2014) Ozan, S.; Gumustekin, S.Performance of stereo imaging methods, which are used to find depth information of a scene, can be adversely affected by surface reflection properties of subjects in the scene and possible change in relative camera and light source positions. In this study a catadioptric multiview imaging system, which is constructed by using planar mirrors, is proposed. Stereo matching problems which are caused by the specular reflections in the scene are highlighted and it is shown that those problems can be significantly alleviated by using polarization images. © 2014 IEEE.Editorial Message From the Mvv Workshop Chairs(IEEE Computer Society, 2012) Tuglular,T.; Linschulte,M.[No abstract available]Article Citation - WoS: 4Citation - Scopus: 7Adaptive Reduced Feedback Links for Distributed Power Allocation in Multicell Miso-Ofdma Networks(IEEE Computer Society, 2014) Özbek, Berna; Le Ruyet, Didier; Pischella, MyleneFor multi-antenna Orthogonal Frequency-Division Multiple Access (OFDMA) based multicell networks, the channel state information (CSI) of all users is required to share among base stations in order to perform distributed power allocation. However, the amount of feedback increases with the number of users, base stations, subcarriers and antennas. Therefore, it is important to perform a selection at the user side to reduce the feedback load and the complexity of resource allocation. In this letter, we propose adaptive reduced feedback links by choosing the users based on their approximate signal to interference noise ratio (SINR) and their locations in the cell to satisfy users' rate constraints. We illustrate the performance results of reduced feedback links by employing distributed resource allocation with link adaptation.Conference Object Citation - Scopus: 3Taylor Series Approximation for Low Complexity Semi-Blind Best Linear Unbiased Channel Estimates for the General Linear Model With Applications To Dtv(IEEE Computer Society, 2004) Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark; Özen, Serdar; Zoltowski, MichaelWe present a low complexity approximate method for semi-blind best linear unbiased estimation (BLUE) of a channel impulse response vector (CIR) for a communication system which utilizes a periodically transmitted training sequence, within a continuous stream of information symbols. The algorithm achieves slightly degraded results at a much lower complexity than directly computing the BLUE CIR estimate. In addition, the inverse matrix required to invert the weighted normal equations to solve the general least squares problem may be precomputed and stored at the receiver. The BLUE estimate is obtained by solving the general linear model, y = Ah + w + n, for h, where w is correlated noise and the vector n is an AWGN process, which is uncorrelated with w. The solution is given by the Gauss-Markoff Theorem as h = (A TC(h) -1A) -1 A TC(h) -1y. In the present work we propose a Taylor series approximation for the function F(h) = (A TC(h) -1A) -1 A TC(h) -1y where, F: R L → R L for each fixed vector of received symbols, y, and each fixed convolution matrix of known transmitted training symbols, A. We describe the full Taylor formula for this function, F (h) = F (h id + ∑ |α|≥1(h - h id) α (∂/∂h) α F(h id) and describe algorithms using, respectively, first, second and third order approximations. The algorithms give better performance than correlation channel estimates and previous approximations used at only a slight increase in complexity. The linearization procedure used is similar to that used in the linearization to obtain the extended Kalman filter, and the higher order approximations are similar to those used in obtaining higher order Kalman filter approximations,