Browsing by Subject "Pre-processing"
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Item Open Access Çok-bileşenli sinyallerin analizi için destek bölge uyarlamalı hermite-gauss açılımı(IEEE, 2011-04) Alp, Yaşar Kemal; Arıkan, Orhan; Özertem, U.Zaman-frekans destek bölgesi orijin etrafında dairesel bir alana uyan bir sinyal bileşeni için, Hermite-Gauss açılımı en az sayıda taban fonsiyonu kullanarak en iyi temsili oluşturur. Ancak, orijinden uzakta ve dairesel olmayan zaman-frekans destek noklarına sahip sinyal bileşenleri için Hermite-Gauss açılımının direk uygulanması, çok fazla sayıda Hermite-Gauss fonksiyonunun kullanımını gerektirir. Bu da, eğer ölçüm sinyali gürültü altında kaydedilmişse ya da birçok sinyal bileşeni içeriyorsa, başarısız bileşen kestirimlerine neden olur. Bu problemi çözmek için sinyal bileşenlerinin destek bölgelerini bulup, zaman-frekans düzleminde orijin civarında, dairesel bir bölgeye oturtan ve bu sayede en az sayıda Hermite-Gauss fonksiyonu kullanarak sinyal bileşenlerini başarılı bir şekilde kestiren, tamamen otomatikleştirilmiş bir önişleme yöntemi önermekteyiz. Önişlemenin ardından, kestirilen bileşenlere ters dönüşümler uygulanarak destek bölgeleri eski yerlerine taşınırItem Open Access Positioning algorithms for cooperative networks in the presence of an unknown turn-around time(IEEE, 2011) Gholami, M.R.; Gezici, Sinan; Ström, E.G.; Rydström, M.This paper addresses the problem of single node positioning in cooperative network using hybrid two-way time-of-arrival and time-difference-of-arrival where, the turn-around time at the target node is unknown. Considering the turn-around time as a nuisance parameter, the derived maximum likelihood estimator (MLE) brings a difficult global optimization problem due to local minima in the cost function of the MLE. To avoid drawbacks in solving the MLE, we obtain a linear two-step estimator using non-linear pre-processing which is algebraic and closed-form in each step. To compare different methods, Cramér-Rao lower bound (CRLB) is derived. Simulation results confirm that the proposed linear estimator attains the CRLB for sufficiently high signal-to-noise ratios. © 2011 IEEE.Item Open Access Reducing MLFMA memory with out-of-core implementation and data-structure parallelization(IEEE, 2013) Hidayetoğlu, Mert; Karaosmanoğlu, Barışcan; Gürel, LeventWe present two memory-reduction methods for the parallel multilevel fast multipole algorithm (MLFMA). The first method implements out-of-core techniques and the second method parallelizes the pre-processing data structures. Together, these methods decrease parallel MLFMA memory bottlenecks, and hence fast and accurate solutions can be achieved for largescale electromagnetics problems.Item Open Access Time-frequency analysis of signals using support adaptive Hermite-Gaussian expansions(Elsevier, 2012-05-18) Alp, Y. K.; Arıkan, OrhanSince Hermite-Gaussian (HG) functions provide an orthonormal basis with the most compact time-frequency supports (TFSs), they are ideally suited for time-frequency component analysis of finite energy signals. For a signal component whose TFS tightly fits into a circular region around the origin, HG function expansion provides optimal representation by using the fewest number of basis functions. However, for signal components whose TFS has a non-circular shape away from the origin, straight forward expansions require excessively large number of HGs resulting to noise fitting. Furthermore, for closely spaced signal components with non-circular TFSs, direct application of HG expansion cannot provide reliable estimates to the individual signal components. To alleviate these problems, by using expectation maximization (EM) iterations, we propose a fully automated pre-processing technique which identifies and transforms TFSs of individual signal components to circular regions centered around the origin so that reliable signal estimates for the signal components can be obtained. The HG expansion order for each signal component is determined by using a robust estimation technique. Then, the estimated components are post-processed to transform their TFSs back to their original positions. The proposed technique can be used to analyze signals with overlapping components as long as the overlapped supports of the components have an area smaller than the effective support of a Gaussian atom which has the smallest time-bandwidth product. It is shown that if the area of the overlap region is larger than this threshold, the components cannot be uniquely identified. Obtained results on the synthetic and real signals demonstrate the effectiveness for the proposed time-frequency analysis technique under severe noise cases.