Browsing by Subject "Processing Time"

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    A compression method based on compressive sampling for 3-D laser range scans of indoor environments
    (Springer, Dordrecht, 2010) Dobrucalı, Oğuzcan; Barshan, Billur
    When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to increase the capacity of the communication channel or the storage medium. We propose a novel compression technique based on compressive sensing, applied to sparse representations of 3-D range measurements. We develop a novel algorithm to generate sparse innovations between consecutive range measurements along the axis of the sensor's motion, since the range measurements do not have highly sparse representations in common domains. Compared with the performances of widely used compression techniques, the proposed method offers the smallest compression ratio and provides a reasonable balance between reconstruction error and processing time. © 2011 Springer Science+Business Media B.V.
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    Fast and accurate analysis of complicated metamaterial structures using a low-frequency multilevel fast multipole algorithm
    (2009-09) Ergül, Özgür; Gürel, Levent
    We present efficient solutions of electromagnetics problems involving realistic metamaterial structures using a low-frequency multilevel fast multipole algorithm (LF-MLFMA). Ordinary implementations of MLFMA based on the diago-nalization of the Green's function suffer from the low-frequency breakdown, and they become inefficient for the solution of metamaterial problems dis-cretized with very small elements compared to the wavelength. We show that LF-MLFMA, which employs multipoles explicitly without diagonalization, significantly improves the solution of metamaterial problems in terms of both processing time and memory. © 2009 IEEE.
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    Particle swarm optimization for SAGE maximization step in channel parameter estimation
    (IET, 2007-11) Bodur, Harun; Tunç, Celal Alp; Aktaş, Defne; Ertürk, Vakur .B.; Altıntaş, Ayhan
    This paper presents an application of particle swarm optimization (PSO) in space alternating generalized expectation maximization (SAGE) algorithm. SAGE algorithm is a powerful tool for estimating channel parameters like delay, angles (azimuth and elevation) of arrival and departure, Doppler frequency and polarization. To demonstrate the improvement in processing time by utilizing PSO in SAGE algorithm, the channel parameters are estimated from a synthetic data and the computational expense of SAGE algorithm with PSO is discussed. (4 pages).