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Item Open Access Deconvolution using Fourier transform phase, ℓ1 and ℓ2 balls, and filtered variation(Elsevier, 2018) Yorulmaz, O.; Çetin, A. EnisShow more In this article, we present a deconvolution software based on convex sets constructed from the phase of the Fourier Transform, bounded ℓ2 energy and ℓ1 energy of a given image. The iterative deconvolution algorithm is based on the method of projections onto convex sets. Another feature of the method is that it can incorporate an approximate total variation bound called filtered variation bound on the iterative deconvolution algorithm. The main purpose of this article is to introduce the open source software called projDeconv v2.Show more Item Open Access Deconvolution using Fourier Transform phase, ℓ1 and ℓ2 balls, and filtered variation(Elsevier B.V., 2018) Yorulmaz, O.; Çetin, A. EnisShow more In this article, we present a deconvolution software based on convex sets constructed from the phase of the Fourier Transform, bounded ℓ2 energy and ℓ1 energy of a given image. The iterative deconvolution algorithm is based on the method of projections onto convex sets. Another feature of the method is that it can incorporate an approximate total variation bound called filtered variation bound on the iterative deconvolution algorithm. The main purpose of this article is to introduce the open source software called projDeconv v2.Show more Item Open Access Deconvolution using projections onto the epigraph set of a convex cost function(IEEE, 2014) Tofighi, Mohammad; Bozkurt, Alican; Köse, K.; Çetin, A. EnisShow more A new deconvolution algorithm based on making orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization problem is lifted by one and sets corresponding to the cost function and observations are defined. If the utilized cost function is convex in RN, the corresponding epigraph set is also convex in RN+1. The deconvolution algorithm starts with an arbitrary initial estimate in RN+1. At each iteration cycle of the algorithm, first deconvolution projections are performed onto the hyperplanes representing observations, then an orthogonal projection is performed onto epigraph of the cost function. The method provides globally optimal solutions for total variation, l1, l2, and entropic cost functions.Show more Item Open Access InGaAs-based high-performance p-i-n photodiodes(IEEE, 2002-03) Kimukin, I.; Bıyıklı, Necmi; Butun, B.; Aytur, O.; Ünlü, S. M.; Özbay, EkmelShow more In this letter, we have designed, fabricated, and characterized high-speed and high efficiency InGaAs-based p-i-n photodetectors with a resonant cavity enhanced structure. The devices were fabricated by a microwave-compatible process. By using a postprocess recess etch, we tuned the resonance wavelength from 1605 to 1558 nm while keeping the peak efficiencies above 60%. The maximum quantum efficiency was 66% at 1572 nm which was in good agreement with our theoretical calculations. The photodiode had a linear response up to 6-mW optical power, where we obtained 5-mA photocurrent at 3-V reverse bias. The photodetector had a temporal response of 16 ps at 7-V bias. After system response deconvolution, the 3-dB bandwidth of the device was 31 GHz, which corresponds to a bandwidth-efficiency product of 20 GHz.Show more Item Open Access Partial FOV Center Imaging (PCI): a robust X-space image reconstruction for magnetic particle imaging(IEEE, 2020) Kurt, Semih; Muslu, Yavuz; Sarıtaş, Emine ÜlküShow more Magnetic Particle Imaging (MPI) is an emerging medical imaging modality that images the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles using their nonlinear response to applied magnetic fields. In standard x-space approach to MPI, the image is reconstructed by gridding the speed-compensated nanoparticle signal to the instantaneous position of the field free point (FFP). However, due to safety limits on the drive field, the field-of-view (FOV) needs to be covered by multiple relatively small partial field-of-views (pFOVs). The image of the entire FOV is then pieced together from individually processed pFOVs. These processing steps can be sensitive to non-ideal signal conditions such as harmonic interference, noise, and relaxation effects. In this work, we propose a robust x-space reconstruction technique, Partial FOV Center Imaging (PCI), with substantially simplified pFOV processing. PCI first forms a raw image of the entire FOV by mapping MPI signal directly to pFOV center locations. The corresponding MPI image is then obtained by deconvolving this raw image by a compact kernel, whose fully-known shape solely depends on the pFOV size. We analyze the performance of the proposed reconstruction via extensive simulations, as well as imaging experiments on our in-house FFP MPI scanner. The results show that PCI offers a trade-off between noise robustness and interference robustness, outperforming standard x-space reconstruction in terms of both robustness against non-ideal signal conditions and image quality.Show more Item Open Access Pasif bistatik radarlarda seyreklik temellli ters evrişim kullanılarak hedef tespiti(IEEE, 2015-05) Arslan, Musa Tunç; Tofighi, Mohammad; Çetin, A. EnisShow more Bu bildiride pasif radar (PR) sistemlerinin menzil çözünürlüğünü artırmak için seyreklik tabanlı bir ters evrişim yöntemi sunulmaktadır. PR sistemlerinin iki boyutlu uyumlu süzgeç çıktısı bir ters evrişim problemli gibi düşünülerek incelenmektedir. Ters evrişim algoritması, hedeflerin zaman kaymaları ve l1 norm benzeri dışbükey maliyet fonksiyonlarının epigraf kümelerini temsil eden hiperdüzlemler üzerine izdüşümü temellidir. Bütün kısıt kümeleri kapalı ve dışbükey olduklarından dolayı yinelemeli algoritma yakınsamaktadır. FM tabanlı PR sistemleri üzerinde benzetim sonuçları sunulmuştur. Algoritma frekans uzayı tabanlı ters evrişim yöntemlerine göre daha yüksek performansa sahiptir.Show more Item Open Access Projections onto the epigraph set of the filtered variation function based deconvolution algorithm(IEEE, 2017) Tofighi, M.; Çetin, A. EnisShow more A new deconvolution algorithm based on orthogonal projections onto the hyperplanes and the epigraph set of a convex cost function is presented. In this algorithm, the convex sets corresponding to the cost function are defined by increasing the dimension of the minimization problem by one. The Filtered Variation (FV) function is used as the convex cost function in this algorithm. Since the FV cost function is a convex function in RN, then the corresponding epigraph set is also a convex set in the lifted set in RN+1. At each step of the iterative deconvolution algorithm, starting with an arbitrary initial estimate in RN+1, first the projections onto the hyperplanes are performed to obtain the first deconvolution estimate. Then an orthogonal projection is performed onto the epigraph set of the FV cost function, in order to regularize and denoise the deconvolution estimate, in a sequential manner. The algorithm converges to the deblurred image.Show more Item Open Access Range resolution improvement in FM-based passive radars using deconvolution(Springer-Verlag London Ltd, 2016) Arslan, M. T.; Tofighi M.; Çetin, A. EnisShow more FM-based passive bistatic radar (PBR) systems suffer from low range resolution because of the low baseband bandwidth of commercial FM broadcasts. In this paper, we propose a range resolution improvement method using deconvolution. The output of the PBR matched filter is processed using a deconvolution algorithm which assumes that targets are isolated, i.e., sparse in the range domain. The deconvolution algorithm is iterative and was implemented by performing successive orthogonal projections onto supporting hyperplanes of the epigraph set of a convex cost function. Simulation examples are presented.Show more Item Open Access Range resolution improvement in passive bistatic radars using deconvolution(Bilkent University, 2015-11) Arslan, Musa TunçShow more Passive radar (PR) systems attract interests in radar community due to its lower cost and power consumption over conventional radars. However, one of the main disadvantages of a PR system is its low range resolution. The reason for this is, the range resolution depends on the bandwidth of the transmitted waveform and in a PR scenario, it is impossible to change transmitted waveform properties of a commercial broadcast. In this thesis, a post processing scheme is proposed to improve the range resolution of an FM broadcast based PR system. In the post processing scheme, the output of the ambiguity function is re-expressed as convolution of the autocorrelation of the transmitted signal and a channel impulse response. Therefore, it is shown that it is possible to use deconvolution methods to compute the channel impulse response using the output of the ambiguity function and the autocorrelation of the transmitted signal. Thus, using deconvolution to solve the channel impulse response provides an increase in the range resolution of the PR system. The method successfully increases the target separation distance and range resolution of a PR system using single FM channel signal. The conventional ambiguity function is able to separate two targets when the targets have about 17 km between each other where as the deconvolution based post processing method can decrease this to about 10 km. The deconvolution based post processing methods also decreases the side lobes around the target when the system uses multi channel FM signals. For a scenario in which three FM channels are employed, the highest side lobe is 1.2 dB below the main target peak and after deconvolution, this highest side lobe decreases to about 10 dB below the main target peak.Show more Item Open Access Range resolution improvement in passive bistatic radars using nested FM channels and least squares approach(SPIE, 2015) Arslan, Musa Tunç; Tofighi, Muhammad; Sevimli, Rasim Akın; Çetin, A. EnisShow more One of the main disadvantages of using commercial broadcasts in a Passive Bistatic Radar (PBR) system is the range resolution. Using multiple broadcast channels to improve the radar performance is offered as a solution to this problem. However, it suffers from detection performance due to the side-lobes that matched filter creates for using multiple channels. In this article, we introduce a deconvolution algorithm to suppress the side-lobes. The two-dimensional matched filter output of a PBR is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making successive projections onto the hyperplanes representing the time delay of a target. Resulting iterative deconvolution algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in an FM based PBR system are presented.Show more Item Open Access Structured least squares problems and robust estimators(IEEE, 2010-10-22) Pilanci, M.; Arıkan, Orhan; Pinar, M. C.Show more A novel approach is proposed to provide robust and accurate estimates for linear regression problems when both the measurement vector and the coefficient matrix are structured and subject to errors or uncertainty. A new analytic formulation is developed in terms of the gradient flow of the residual norm to analyze and provide estimates to the regression. The presented analysis enables us to establish theoretical performance guarantees to compare with existing methods and also offers a criterion to choose the regularization parameter autonomously. Theoretical results and simulations in applications such as blind identification, multiple frequency estimation and deconvolution show that the proposed technique outperforms alternative methods in mean-squared error for a significant range of signal-to-noise ratio values.Show more