Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/47

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Citation Count: 0
Abstraction in FPGA implementation of neural networks
(World Scientific and Engineering Academy and Society, 2008) Öğrenci, Arif Selçuk
A model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware description languages. The synthesis will be based on the tools supplied by the FPGA vendors. The results indicate that the method can be utilized and it can be further improved to create a general methodology that bridges the gap between hardware and software in embedded system design.
Citation Count: 6
Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing
(IEEE, 2014) Erküçük, Serhat; Erküçük, Serhat; Çırpan, Hakan Ali
In wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE) compression ratio and signal-to-noise ratio (SNR) and compare it with the conventionally used basis pursuit approach (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing.
Citation Count: 1
Across dimensions: Two- and three-dimensional phase transitions from the iterative renormalization-group theory of chains
(2020) Keçoğlu, İbrahim; Berker, A. Nihat
Sharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase transition or nonzero magnetization, but the method reflects crossover from temperaturelike to fieldlike renormalization-group flows as the mechanism for the higher-dimensional phase transitions. The magnetization of each chain acts, via the interaction constant, as a magnetic field on its neighboring chains, thus entering its renormalization-group calculation. The method is highly flexible for wide application.
Citation Count: 0
Advanced signal processing algorithms for wireless communications
(Springer-Verlag Berlin, 2006) Panayırcı, Erdal; Çırpan, Hakan Ali
Traditional wireless technologies are not well suited to meet the extremely demanding requirements of providing the very high data rates with the ubiquity mobility and portability characteristic of cellular systems. Some fundamental barriers related to the nature of the radio channel as well as the limited bandwidth availability at the frequencies of interest stand in the way. Unique sets of efficient advanced signal processing algorithms and techniques is the one of the primary enablers that will allow lifting these limits primarily due to the impressive advent of low cost and low power digital signal processors. As an application of advanced signal processing techniques we will consider the solution of blind phase noise estimation and data detection problem via a computationally efficient sequential Monte Carlo (SMC) methodology in this paper.
Citation Count: 0
An Alternative Approach To Design Lumped Element Delay Equalizers
(Istanbul Univ Fac Engineering, 2015) Şengül, Metin Y.
In this paper an algorithm has been proposed to design lumped element delay equalizers which is considered as a single block as opposed to the existing methods in literature. Then after obtaining the desired delay performance the designed delay equalizer is divided and realized as cascaded first-order and/or second-order all-pass circuits. An example is given to illustrate the utilization of the proposed algorithm.
Citation Count: 0
Alternative Transducer Power Gain Expression in Broadband Matching Network Designs
(IEEE, 2016) Şengül, Metin Y.
In this paper a reflection coefficient based transducer power gain expression has been derived which is an alternative to the impedance based expression exists in the literature. A broadband double matching problem is solved by using the derived gain expression and the obtained performance has been compared with the performance obtained via the existing expression.
Citation Count: 0
Amplitude and Frequency Modulations with Cellular Neural Networks
(Springer, 2015) Tander, Baran; Özmen, Atilla
Amplitude and frequency modulations are still the most popular modulation techniques in data transmission at telecommunication systems such as radio and television broadcasting gsm etc. However the architectures of these individual systems are totally different. In this paper it is shown that a cellular neural network with an opposite-sign template can behave either as an amplitude or a frequency modulator. Firstly a brief information about these networks is given and then the amplitude and frequency surfaces of the generated quasi-sine oscillations are sketched with respect to various values of their cloning templates. Secondly it is proved that any of these types of modulations can be performed by only varying the template components without ever changing their structure. Finally a circuit is designed simulations are presented and performance of the proposed system is evaluated. The main contribution of this work is to show that both amplitude and frequency modulations can be realized under the same architecture with a simple technique specifically by treating the input signals as template components.
Citation Count: 0
Analysis and Optimization of Matching Networks-I Getting Started with ADS
(Springer-Verlag Berlin, 2008) Şengül, Metin Y.
[Abstract Not Available]
Citation Count: 0
Analysis and Optimization of Matching Networks-II Getting Started with Microwave Office
(Springer-Verlag Berlin, 2008) Şengül, Metin Y.
[Abstract Not Available]
Citation Count: 4
Analysis of Extended Busy Tone Performance for Coexistence between WRAN and WLAN TVWS Networks
(IEEE, 2015) Baykaş, Tunçer; Erküçük, Serhat; Baykaş, Tunçer
TV White Spaces indicate spectrum bands which were reserved for licensed terrestrial TV broadcasting and opened to unlicensed use under regulatory conditions. One important regulation which is common in all regulatory domains is no harmful interference is created to licensed devices. On the other hand interference between unlicensed devices is not regulated. As a result system designers developed new methods to improve coexistence between TVWS networks. Extended busy tone one of such methods is designed for coexistence between wireless regional area and wireless local area networks based on IEEE 802.22 and 802.11af standards respectively. In this paper we analyse the performance of extended busy tone at different range conditions and verify via simulations under realistic conditions. Our results indicate that the method can reduce interference considerably at intermediate distances and enable networks to operate without a significant reduction in throughput.
Citation Count: 5
Analysis of Mixed-Element Structures Formed With Shunt Capacitors Separated by Transmission Lines
(IEEE-Inst Electrical Electronics Engineers Inc, 2019) Şengül, Metin Y.; Çakmak, Gökhan
In this brief, the analysis of mixed-element structures formed with shunt capacitors separated by commensurate transmission lines is performed first time in the literature. First, a low-pass lumped-element ladder network is considered. Then the series inductors are replaced with commensurate transmission lines. As a result, a practically important mixed-element structure is obtained. Then the description of the structure by means of two frequency variables (one for shunt capacitors and one for transmission lines) is detailed: Explicit expressions for the coefficients of the descriptive two-variable polynomials in terms of the coefficients of the single variable boundary polynomials are derived for various numbers of elements, which are obtained first time in the literature. Finally, a mixed-element broadband matching network is designed to illustrate the usage of the obtained expressions. If it is preferred not to have shunt capacitors, they can be replaced with open-ended stubs via Richard's transformation. So the resultant circuit is extremely suitable for microstrip fabrication.
Citation Count: 0
Analytic solution of the Feldtkeller equation
(Elsevier GMBH Urban & Fischer Verlag, 2009) Şengül, Metin Y.
In every reflectance-based application like broadband matching circuit modeling etc. a nonlinear equation following from energy conservation the Feldtkeller equation must be solved in order to obtain real networks. In the literature however there is no analytic solution available but only numerical solutions. Consequently the resulting error depends on the accuracy of the numerical tools. In this paper an analytic solution is proposed which is based on the modified ABCD-parameters of a lossless reciprocal two-port network. An algorithm is presented and examples are included to illustrate the implementation of the analytical method. (C) 2008 Elsevier GmbH. All rights reserved.
Citation Count: 1
Anomaly Detection in Walking Trajectory
(IEEE, 2018) Öğrenci, Arif Selçuk
Analysis of the walking trajectory and the detection of anomalies in this trajectory, provide important benefits in the fields of health and security. In this work, two methods to detect anomalies in trajectories, are compared. Firstly, an unsupervised method is used where the conformance among trajectories are taken into consideration. Trajectories that deviate from others are qualified as anomalies. Secondly, the points in the trajectories are considered as a time series. Artifical neural networks performing supervised learning based on the backpropagation algorithm are used. The results are compared, and the points to be enhanced are highlighted.
Citation Count: 2
Anomaly detection in walking trajectory [Yürüyüş yörüngesinde anormallik algılama]
(Institute of Electrical and Electronics Engineers Inc., 2018) Öğrenci, Arif Selçuk
Analysis of the walking trajectory and the detection of anomalies in this trajectory provide important benefits in the fields of health and security. In this work two methods to detect anomalies in trajectories are compared. Firstly an unsupervised method is used where the conformance among trajectories are taken into consideration. Trajectories that deviate from others are qualified as anomalies. Secondly the points in the trajectories are considered as a time series. Artifical neural networks performing supervised learning based on the backpropagation algorithm are used. The results are compared and the points to be enhanced are highlighted.
Citation Count: 13
Bayesian Compressive Sensing For Primary User Detection
(Inst Engineering Technology-IET, 2016) Erküçük, Serhat; Erküçük, Serhat; Cirpan, Hakan Ali
In compressive sensing (CS)-based spectrum sensing literature most studies consider accurate reconstruction of the primary user signal rather than detection of the signal. Furthermore possible absence of the signal is not taken into account while evaluating the spectrum sensing performance. In this study Bayesian CS is studied in detail for primary user detection. In addition to assessing the signal reconstruction performance and comparing it with the conventional basis pursuit approach and the corresponding lower bounds signal detection performance is also considered both analytically and through simulation studies. In the absence of a primary user signal the trade-off between probabilities of detection and false alarm is studied as it is equally important to determine the performance of a CS approach when there is no active primary user. To reduce the computation time and yet achieve a similar detection performance finally the effect of number of iterations is studied for various systems parameters including signal-to-noise-ratio compression ratio mean value of accumulated energy and threshold values. The presented framework in this study is important in the overall implementation of CS-based approaches for primary user detection in practical realisations such as LTE downlink OFDMA as it considers both signal reconstruction and detection.
Citation Count: 3
Bayesian compressive sensing for ultra-wideband channel estimation: algorithm and performance analysis
(Springer, 2015) Erküçük, Serhat; Erküçük, Serhat; Çırpan, Hakan Ali
Due to the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) sparse structure of standardized IEEE 802.15.4a channel models (ii) signal-to-noise ratio (SNR) regions and (iii) number of measurements on the BCS channel estimation performance and compare them to the results of -norm minimization based estimation which is widely used for sparse channel estimation. We also provide a lower bound on mean-square error (MSE) for the biased BCS estimator and compare it with the MSE performance of implemented BCS estimator. Moreover we study the computation efficiencies of BCS and -norm minimization in terms of computation time by making use of the big- notation. The study shows that BCS exhibits superior performance at higher SNR regions for adequate number of measurements and sparser channel models (e.g. CM-1 and CM-2). Based on the results of this study the BCS method or the -norm minimization method can be preferred over the other one for different system implementation conditions.
Citation Count: 6
Bayesian compressive sensing for ultra-wideband channel models
(IEEE, 2012) Erküçük, Serhat; Erküçük, Serhat; Cirpan, Hakan Ali
Considering the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) sparse structure of standardized IEEE 802.15.4a channel models (ii) signal-to-noise ratio (SNR) regions and (iii) number of measurements on the BCS channel estimation performance and compare them to the results of l(1)-norm minimization based estimation which is widely used for sparse channel estimation. The study shows that BCS exhibits superior performance at higher SNR regions only for adequate number of measurements and sparser channel models (e. g. CM1 and CM2). Based on the results of this study BCS method or the l(1)-norm minimization method can be preferred over the other for different system implementation conditions.
Citation Count: 1
Bayesian estimation of discrete-time cellular neural network coefficients
(TUBITAK Scientific & Technical Research Council Turkey, 2017) Şenol, Habib; Özmen, Atilla; Şenol, Habib
A new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network coefficients. A posterior probability density function (PDF) is composed using the likelihood and prior PDFs derived from the system model and prior information respectively. This posterior PDF is used to draw samples with the help of the Metropolis algorithm a special case of the Metropolis--Hastings algorithm where the proposal distribution function is symmetric and resulting samples are then averaged to find the minimum mean square error (MMSE) estimate of the network coefficients. A couple of image processing applications are performed using these estimated parameters and the results are compared with those of some well-known methods.
Citation Count: 1
Beacons for Indoor Positioning
(IEEE, 2017) Cay, Elif; Mert, Yeliz; Bahcetepe, Ali; Akyazi, Bugra Kagan; Öğrenci, Arif Selçuk
This work aims to develop a system for the tracking and control of elderly or handicapped people in an indoor environment. We have developed both a special box using an Arduino board and a mobile application on Android to determine the location of the target based on the Bluetooth Low Energy signals transmitted by special Beacons which are placed in the area of interest. Both systems are used to determine the position of the person and to monitor any event that would cause an alert. Those events can be a long stay in a fixed position or the entry into pre-defined forbidden zones. The location data will be stored in a database for further processing. Alerts can trigger messages to be sent to local authorities and/or relatives of the people. Measurements and test results are discussed regarding their performance. It is clear that more research and development is necessary for obtaining reliable products.
Citation Count: 1
Blind-phase noise estimation in OFDM systems by sequential Monte Carlo method
(John Wiley and Sons Ltd, 2006) Panayırcı, Erdal; Çırpan, Hakan Ali; Moeneclaey, Marc; Noels, Nele
One of the main drawbacks of orthogonal frequency division multiplexing (OFDM) systems is the phase noise (PN) caused by the oscillator instabilities. Unfortunately due to the PN the most valuable feature namely orthogonality between the carriers is destroyed resulting in a significant degradation in the performance of OFDM systems. In this paper based on a sequential Monte Carlo method (particle filtering) a computationally efficient algorithm is presented for estimating the residual phase noise blindly generated at the output of the phase tracking loop employed in OFDM systems. The basic idea is to treat the transmitted symbols as 'missing data' and draw samples sequentially of them based on the observed signal samples up to time t. This way the Bayesian estimates of the phase noise is obtained through these samples sequentially drawn together with their importance weights. The proposed receiver structure is seen to be ideally suited for highspeed parallel implementation using VLSI technology. The performance of the proposed approaches are studied in terms of average mean square error. Through experimental results the effects of an initialisation on the tracking performance are also explored. Copyright (c) 2006 AEIT.

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