Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7755
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Conference Object Approximate Best Linear Unbiased Channel Estimation for Multi-Antenna Frequency Selective Channels With Applications To Digital Tv Systems(SPIE, 2004) Özen, Serdar; Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark J.; Zoltowski, Michael D.We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication receivers with multiple-antenna. Our algorithm is best suited for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols, and the receivers for this particular system are expected work in a severe frequency selective multipath environment with long delay spreads relative to the length of the training sequence. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.Master Thesis Parameter Estimation for Linear Dynamical Systems With Applications To Experimental Modal Analysis(Izmir Institute of Technology, 2008) Tanyer, İlker; Özen, SerdarIn this study the fundamentals of structural dynamics and system identification have been studied. Then some fundamental parameter estimation algorithms in the literature are provided. These algorithms will be applied to an experimental and an artificial system to extract their structural properties. Consequently, the main objective of this study is constructing the mathematical model of a structure by using only the measurement data.To process measurement data, three fundamental modal analysis algorithms are examined. Least-Squares Complex Exponential(LSCE), Eigensystem Realization Algorithm( ERA) and Polyreference Frequency Domain(PFD) algorithms are implemented in MATLAB environment. We applied these algorithms to artificial and experimental data, then we compared the performance of these algorithms. State estimation for linear dynamical systems have also been studied, and details of the Kalman filter as a state estimator are provided. Kalman filter as a state estimator has been integrated with the ERA algorithm and the performance of the Kalman-ERA is provided.