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Publication Metadata only Exploiting the power of GPUs for multi-gigabit wireless baseband processing(2010) Kocak, Taskin; Hinitt, Nicholas; Kocak, Taskin, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Hinitt, Nicholas, Department of Electrical and Electronic Engineering, University of Bristol, Bristol, United KingdomIn this paper, we explore the feasibility of achieving gigabit baseband throughput using the vast computational power offered by the graphics processors (GPUs). One of the most computationally intensive functions commonly used in baseband communications, the Fast Fourier Transform (FFT) algorithm, is implemented on an NVIDIA GPU using their general-purpose computing platform called the Compute Unified Device Architecture (CUDA). The paper, first, investigates the implementation of an FFT algorithm using the GPU hardware and exploiting the computational capability available. It then outlines the limitations discovered and the methods used to overcome these challenges. Finally a new algorithm to compute FFT is proposed, which reduces interprocessor communication, and it is further optimized by improving memory access, enabling the processing rate to exceed 4 Gbps, achieving a processing time of a 512-point FFT in less than 200 ns. © 2010 IEEE. © 2010 Elsevier B.V., All rights reserved.Publication Metadata only Defect-aware nanocrossbar logic mapping using Bipartite Subgraph Isomorphism & canonization(2010) Gören, Sezer; Uǧurdaǧ, Hasan Fatih; Palaz, Okan; Gören, Sezer, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Uǧurdaǧ, Hasan Fatih, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Palaz, Okan, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyThis paper addresses the NP-complete problem of mapping a logic function on to a nanocrossbar with a known defect map. We first show that this problem can be transformed into a Bipartite SubGraph Isomorphism (BSGI) problem. Then we present our proposed KNS-2DS algorithm, which canonizes both graphs in N 2 time (N being the number of nodes) and then matches them in N 3 time in the worst case. KNS-2DS uses a K-Neighbor Sort (KNS) to initialize our main contribution 2D-Sort (2DS). 2DS is an iterative rough canonizer that lets a straight forward matching algorithm complete the job. Our algorithm offers very short run-times (due to canonization) compared to previous work and has success on all benchmarks. KNS-2DS is also novel from the perspective of the BSGI problem in the sense that it is based on canonization but not on a search tree with backtracking. © 2010 IEEE. © 2010 Elsevier B.V., All rights reserved.Publication Metadata only Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform(2010) Serbes, Görkem; Aydın, Nizamettin; Serbes, Görkem, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, TurkeyEarly and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB). © 2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Design of optical devices using frequency domain solvers(2010) Ŝimŝek, Ergün; Liu, Qing Huo; Ŝimŝek, Ergün, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Liu, Qing Huo, Pratt School of Engineering, Durham, United StatesThis work deals with efficient frequency domain solvers specifically developed to design optical and plasmonic devices. Homogeneous and inhomogeneous objects embedded in multilayered media are analyzed using Method of Moment (MoM) and hybrid MoM-Finite Element Method (FEM), respectively. The capability of working with materials of complex permittivity makes these algorithms valid and useful for both microwave and optical regimes. Based on the good match between numerical results obtained with these algorithms and the ones found in the literature, we propose an optical antenna optimum for a semiconductor laser diode operating at a wavelength of 830 nm and an infrared sensor compatible with present silicon technology based optical devices. © 2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Open Access Predicting existence of mycobacterium tuberculosis on patients using data mining approaches(2011) Uçar, Tamer; Karahoca, Adem; Uçar, Tamer, Department of Software Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Karahoca, Adem, Department of Software Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyA Correct diagnosis of tuberculosis (TB) can be only stated by applying a medical test to patient's phlegm. The result of this test is obtained after a time period of about 45 days. The purpose of this study is to develop a data mining(DM) solution which makes diagnosis of tuberculosis as accurate as possible and helps deciding if it is reasonable to start tuberculosis treatment on suspected patients without waiting the exact medical test results or not. In this research, we proposed the use of Sugeno-type adaptive-network-based fuzzy inference system (ANFIS) to predict the existence of mycobacterium tuberculosis. 667 different patient records which are obtained from a clinic are used in the entire process of this research. Each of the patient records consist of 30 separate input parameters. ANFIS model is generated by using 500 of those records. We also implemented a multilayer perceptron and PART model using the same data set. The ANFIS model classifies the instances with an RMSE of 18% whereas Multilayer Perceptron does the same classification with an RMSE of % 19 and PART algorithm with an RMSE of % 20. ANFIS is an accurate and reliable method when compared with Multilayer Perceptron and PART algorithms for classification of tuberculosis patients. This study has contribution on forecasting patients before the medical tests. © 2010 Published by Elsevier Ltd. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only A fast power allocation algorithm for MIMO relay channels, MIMO aktarma kanallarinda güç tahsisi i̇çin hizli bir algoritma(2011) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Bahçeşehir Üniversitesi, Istanbul, TurkeyBy assuming full-duplex mode, we consider a MIMO relay channel where the receivers have perfect channel state information (CSI) and the transmitters have partial CSI. Lower bound achieving transmit covariance matrices are derived using an iterative algorithm. Lower bound to the capacity is analyzed for three cases depending on the channel covariance matrix. In the first case, lower bound on the capacity is equal to the capacity of the link from source to relay. In the second case, lower bound on the capacity is equal to the multi access channel capacity from source and relay to the destination. In the last case, lower bound on the capacity depends on both multi access channel and source to relay channel. In that case, under a certain practical channel assumption, we propose a fast power allocation algorithm. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Combining Haar feature and skin color based classifiers for face detection(2011) Erdem, Cigdem Eroglu; Ulukaya, Sezer; Karaali, Ali; Erdem, Tanju Tanju; Erdem, Cigdem Eroglu, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ulukaya, Sezer, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Karaali, Ali, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Tanju Tanju, Electrical and Electronics Engineering, Özyeğin Üniversitesi, Istanbul, TurkeyThis paper presents a hybrid method for face detection in color images. The well known Haar feature-based face detector developed by Viola and Jones (VJ), that has been designed for gray-scale images is combined with a skin-color filter, which provides complementary information in color images. The image is first passed through a Haar-Feature based face detector, which is adjusted such that it is operating at a point on its ROC curve that has a low number of missed faces but a high number of false detections. Then, using the proposed skin color post-filtering method many of these false detections can be eliminated easily. We also use a color compensation algorithm to reduce the effects of lighting. Our experimental results on the Bao color face database show that the proposed method is superior to the original VJ algorithm and also to other skin color based pre-filtering methods in the literature in terms of precision. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Achieving the lower bound of fading MIMO relay channels with covariance feedback at the transmitters(2011) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this paper, we consider a full-duplex mode MIMO relay channel for decode and forward strategy where the receivers have perfect channel state information (CSI) and the transmitters have only covariance feedback at the transmitters. We derive a lower bound to the ergodic capacity for this scenario and propose an iterative algorithm that finds lower bound achieving transmit covariance matrices of the source and relay nodes. The solution of the optimization problem in the lower bound expression is given for three cases depending on channel covariance matrices. For one of these cases, it seems that an efficient and fast algorithm achieving the lower bound is not possible. However, under a certain practical channel assumption, we propose a power allocation algorithm that gives a solution much faster than classical convex optimization methods. Moreover, we show that this fast algorithm results in a data rate which is very close to the lower bound to the capacity. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Multipose face detection using Zernike moment invariants, Zernike moment deǧi̇şmezleri̇ i̇le pozdan baǧimsiz yüz tespi̇ti̇(2012) Karaali, Ali; Erdem, Cigdem Eroglu; Ulukaya, Sezer; Karaali, Ali, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ulukaya, Sezer, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe propose a new efficient technique for localization of faces in arbitrary images. The technique is based on segmentation of images into skin colored blobs, which is followed by computation of scale, translation and rotation invariant moment-based features to learn a statistical model of faces and non-face regions. The superiority of the method to the state-of-the-art face detection methods is its ability to detect non-frontal faces in a person independent way. Experimental results on CVL database show that the proposed algorithm gives higher true positive rates as compared to the well-known Viola-Jones face detector. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Extracellular spike detection with resonance based signal decomposition, Rezonans esasli i̇şaret ayriştirmasi kullanilarak hücre dişi si̇ni̇rsel i̇ǧneci̇k tespi̇ti̇(2012) Serbes, Görkem; Kocatürk, Mehmet; Gülçür, Halil Ö.; Aydın, Nizamettin; Serbes, Görkem, Bahçeşehir Üniversitesi, Istanbul, Turkey, Boğaziçi Üniversitesi, Bebek, Turkey; Kocatürk, Mehmet, Boğaziçi Üniversitesi, Bebek, Turkey; Gülçür, Halil Ö., Boğaziçi Üniversitesi, Bebek, Turkey; Aydın, Nizamettin, Bilgisayar Mühendisliǧi Bölümü, Yıldız Teknik Üniversitesi, Istanbul, TurkeyNeuronal spike detection is an essential pre-processing step for the analysis of extracellular brain signals in neuroscience. In resonance based signal decomposition, analyzed signal can be expressed as the sum of a 'high-resonance' and 'low-resonance component'. A high-resonance component can be thought as a signal consisting of sustained oscillations and a low-resonance component can be thought as a signal consisting of non-oscillatory transients. The morphology of neuronal spikes has transient character and neuronal spikes can be thought as low-resonance component in resonance-based signal decomposition. In this study a novel algorithm for detecting extracellular spikes using resonance based signal decomposition with an adaptive amplitude threshold is proposed. The proposed algorithm is tested on synthetic data and compared with the conventional threshold selection method. The results show that proposed method outperforms traditional amplitude thresholding method © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.
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