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Publication Metadata only A multi-window fractional evolutionary spectral analysis(Institute of Electrical and Electronics Engineers Inc., 2003) Cekic, Yalcin; Akan, Aydin I.; Cekic, Yalcin, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Akan, Aydin I., Department of Electrical Engineering, Istanbul Üniversitesi, Istanbul, TurkeyIn this work, we present a multiple window Evolutionary Spectral analysis on a non-rectangular time-frequency lattice based on a discrete fractional Gabor expansion. The traditional Gabor expansion uses a fixed, and rectangular time-frequency plane tiling. Many of the practical signals such as speech, music, etc., require a more flexible, non-rectangular time-frequency lattice for a compact representation. The proposed method uses a set of basis functions that are related to the fractional Fourier basis and generate a parallelogram-shaped tiling. Simulation results are given to illustrate the performance of our algorithm. © 2022 Elsevier B.V., All rights reserved.Publication Metadata only Harmonic analysis via wavelet packet decomposition using special elliptic half-band filters(2004) Eren, Levent; Ünal, Mehmet; Devaney, Michael Joseph; Demidenko, S.; Ottoboni, R.; Petri, D.; Piuri, V.; Weng, D.C.T.; Eren, Levent, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ünal, Mehmet, Department of Mathematics, Bahçeşehir Üniversitesi, Istanbul, Turkey; Devaney, Michael Joseph, College of Engineering, Columbia, United StatesThe Fast Fourier Transform is the most widely used power system harmonic analysis tool in real time power metering due to its computational efficiency. Recently, an alternate method, wavelet packet decomposition, has been applied to power system signals to meter voltage and current harmonics. Although the new method provides better analysis, the computational complexity of wavelet packet decomposition places a limitation on its use in real time metering. This paper proposes the use of all-pass implemented half-band elliptic IIR filters in the wavelet packet decomposition of power system signals. The proposed implementation reduces the computational complexity to levels comparable to Fast Fourier Transform. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Power driven reconfigurable complex continuous wavelet transform processor(2006) Aydın, Nizamettin; Arslan, Tughrul S.; Aydın, Nizamettin, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Arslan, Tughrul S., School of Engineering and Electronics, The University of Edinburgh, Edinburgh, United KingdomA low power VLSI implementation of reconfigurable complex Continuous Wavelet Transform (CWT) algorithm to generate the two dimensional time scale representation of a one dimensional signal is introduced The CWT is computationally intensive process. The CWT processor presented in this paper employs a bank of correlators. The correlators which are not needed in a certain transform are disabled to save power. So power consumption of the CWT processor depends on the number of scales. The processor has been implemented and synthesized using ALCATEL 0.35p technology. Mallab, RTL, and netlist simulation results verify that the implemented algorithm has the potential to be utilized as a wavelet coprocessor for fast time-scale analysis in real-time. © 2006 IEEE. © 2008 Elsevier B.V., All rights reserved.Publication Metadata only An improved odor recognition system using learning vector quantization with a new discriminant analysis(2007) Temel, Turgay; Karlik, Bekir; Temel, Turgay, Engineering Faculty, Bahçeşehir Üniversitesi, Istanbul, Turkey; Karlik, Bekir, Computer Engineering Department, Fatih Üniversitesi, Istanbul, TurkeyA new pre-processing algorithm for improved discrimination of odor samples is proposed. The pre-processed odor sample outputs from two sensors are input using a learning-vector quantization (LVQ) classifier as a means of odor recognition to be employed within electronic nose applications. The proposed algorithm brings out highly scattered classes while minimizing the within-class scatter of the samples given an odor class. LVQ is observed to operate robustly and reliably in terms of variation of parameters of interest, mainly a learning parameter. Due to the increased performance along with computational simplicity and robustness, the scheme is suitable to sample-by-sample identification of olfactory sensory data and can be easily adapted to hierarchical processing with other sensory data in real-time. © ICS AS CR 2007. © 2008 Elsevier B.V., All rights reserved.Publication Metadata only An adaptive approach to the segmentation of dce-mr images of the breast: Comparison with classical thresholding algorithms(2007) Kaleli, Fatih; Aydın, Nizamettin; Ertaş, Gökhan; Gülçür, Halil Ö.; Kaleli, Fatih, Engineering Faculty, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydın, Nizamettin, Engineering Faculty, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ertaş, Gökhan, Biomedical Engineering Institute, Boğaziçi Üniversitesi, Bebek, Turkey; Gülçür, Halil Ö., Biomedical Engineering Institute, Boğaziçi Üniversitesi, Bebek, TurkeyThe segmentation of MR images has been playing an important role to improve the detection and diagnosis of breast cancer. Main problem in breast images is the identification of the boundary between chest wall and breast tissue. Minimizing the effects of patient motion is also important step in segmentation process. In image processing, there are many different segmentation algorithms. The most common used method among them is thresholding. However, classic thresholding methods are not effective for axial MR breast images completely because of the fact that the sequence artifacts in axial MR breast images are very high. For this reason, we have proposed a regional thresholding algorithm to segment MR images successfully. The outstanding problem is how to obtain an automatic procedure for detecting boundary between breast tissue and chest wall. © 2007 IEEE. © 2008 Elsevier B.V., All rights reserved.Publication Metadata only Bearing fault detection in adjustable speed drives via a support vector machine with feature selection using a genetic algorithm(2008) Teotrakool, Kaptan; Devaney, Michael Joseph; Eren, Levent; Teotrakool, Kaptan, Department of Electrical & Computer Engineering, University of Missouri, Columbia, United States; Devaney, Michael Joseph, Department of Electrical & Computer Engineering, University of Missouri, Columbia, United States; Eren, Levent, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyThis paper presents a novel method to detect bearing defects in Adjustable Speed Drives (ASD's). The harmonics in pulse-width-modulation (PWM) input voltage waveforms and EMI noise in ASD systems make bearing fault detection more dfficult. The proposed method accomplishes bearing fault detection in ASD's by combining Motor Current Signature Analysis (MCSA), Wavelet Packet Decomposition (WPD), a Genetic Algorithm (GA), and a Support Vector Machine (SVM). The SVM in conjunction with the GA is applied to the rms values of the wavelet packet coefficients to obtain significant wavelet packet nodes which produce optimal classifiers for classifying both healthy and defective bearings in ASD systems. ©2008 IEEE. © 2008 Elsevier B.V., All rights reserved.Publication Metadata only Computational complexity investigations for∈high-dimensional model representation algorithms used in multivariate interpolation problems(2009) Tunga, Mehmet Alper; Demiralp, Metin; Mastorakis, N.; Sakellaris, J.; Tunga, Mehmet Alper, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Demiralp, Metin, Informatics Institute, İstanbul Teknik Üniversitesi, Istanbul, TurkeyIn multivariate interpolation problems, increase in both the number of independent variables of the sought function and the number of nodes appearing in the data set causes computational and mathematical difficulties. It may be a better way to deal with less variate partitioned data sets instead of an N-dimensional data set in a multivariate interpolation problem. New algorithms such as high-dimensional model representation (HDMR), generalized HDMR, factorized HDMR, hybrid HDMR are developed or rearranged for these types of problems. Up to now, the efficiency of the methods in mathematical sense was discussed in several papers. In this work, the efficiency of these methods in computational sense will be discussed. This investigation will be done by using several numerical implementations. © 2009 Springer Science+Business Media LLC. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Binary sequences and association graphs for fast detection of sequential patterns(2009) Mimaroglu, Selim N.; Simovici, Dan A.; Mimaroglu, Selim N., Bahçeşehir Üniversitesi, Istanbul, Turkey; Simovici, Dan A., University of Massachusetts Boston, Boston, United StatesWe develop an efficient algorithm for detecting frequent patterns that occur in sequence databases under certain constraints. By combining the use of bit vector representations of sequence databases with association graphs we achieve superior time and low memory usage based on a considerable reduction of the number of candidate patterns. © CEPAD 2009. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only High capacity image watermarking in the joint spatio-frequency domain(2009) Ozturk, Mahmut; Akan, Aydin I.; Yalçin Çekiç; Ozturk, Mahmut, Department of Electrical and Electronics Engineering, Istanbul Üniversitesi, Istanbul, Turkey; Akan, Aydin I., Department of Electrical and Electronics Engineering, Istanbul Üniversitesi, Istanbul, Turkey; Yalçin Çekiç, null, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyWatermarking techniques are proposed as a solution to copyright protection of digital media files. Watermarking algorithms are mainly concentrated on spatial or spectral domains. In this work, a robust and high capacity watermarking method that is based on spatio-frequency (SF) representations is presented. We use the Discrete Evolutionary Transform (DET) to represent an image in the SF domain. A watermark is embedded onto selected coefficients in the joint SF domain. Hence by combining the advantages of spatial and spectral domain watermarking methods, a robust, invisible, secure and high capacity watermarking method is presented. Simulations results yield that the proposed algorithm is robust to many signal processing attacks and outperforms several previous watermarking techniques. © 2010 Elsevier B.V., All rights reserved.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.