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Articles 751 - 780 of 3020
Full-Text Articles in Physical Sciences and Mathematics
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetic resonance conductivity tensor imaging (MRCTI) reconstructs high-resolution anisotropic conductivity images, which are proved to have critical importance in radio-oncological imaging as well as source localization fields. In the MRCTI technique, linearly independent current injections are applied to the region to be imaged and resulting magnetic flux densities are measured using magnetic resonance imaging techniques. In this study, a novel iterative reconstruction algorithm based on a sensitivity matrix approach is proposed and tested using both simulated and experimental measurements. Obtained results show that the proposed technique can reconstruct anisotropic conductivity images with high and position-independent spatial resolution in addition to …
Optimal Contract Pricing Of Load Aggregators For Direct Load Control In Smartdistribution Systems, Ali Shayegan-Rad, Ali Zangeneh
Optimal Contract Pricing Of Load Aggregators For Direct Load Control In Smartdistribution Systems, Ali Shayegan-Rad, Ali Zangeneh
Turkish Journal of Electrical Engineering and Computer Sciences
Distribution system operators (DSOs) are interested in demand side participation programs as an efficient and secure resource to manage electricity supply and demand. However, it is usually difficult for DSOs to aggregate demand response of large/small consumers. Thus, in some electricity markets, an entity called an aggregator is defined to aggregate the load response of consumers. In this paper a bilevel scheduling model is proposed to determine the long-term optimal contract price between the DSO and aggregator for executing direct load control in smart distribution systems. The DSO and aggregator are considered as two different agents with individual objectives in …
Optimal Placement Of Switching And Protection Devices In Radial Distribution Networks To Enhance System Reliability Using The Ahp-Pso Method, Masoud Amohadi, Mahmud Fotuhi Firuzabad
Optimal Placement Of Switching And Protection Devices In Radial Distribution Networks To Enhance System Reliability Using The Ahp-Pso Method, Masoud Amohadi, Mahmud Fotuhi Firuzabad
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new method to determine the optimal number and locations of autorecloser and sectionalizer switches (AR/S) in distribution networks. The costs of AR/S investment, switch maintenance, and undistributed energy as well as reliability coefficients are considered in the objective function. Reliability parameters such as SAIFI, SADI, MAIFI, and ENS are evaluated in the case study system. As a new method, the weights of the reliability parameters are obtained by decision-makers using the analytical hierarchy process (AHP). The optimal size, type, and location of automatic switches are determined by minimizing the objective function using the particle swarm optimization …
Improved Vsm Control Of Pmsg-Based Wind Farms For Transient Stability Enhancement, Mohamed Abbes, Ines Mehouachi, Souad Chebbi
Improved Vsm Control Of Pmsg-Based Wind Farms For Transient Stability Enhancement, Mohamed Abbes, Ines Mehouachi, Souad Chebbi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper analyzes the optimal control strategy of PMSG-based wind farms during faults in order to improve the transient stability of a power system with a high penetration rate of wind power. The investigated control strategies are the unity power factor (UPF), reactive power control (RPC), and particularly the concept of virtual synchronous machine (VSM). The transient stability level is assessed using the critical clearing time index, which was calculated based on trajectory sensitivity analysis. In light of the obtained results, it was found that RPC gives the best transient stability level, followed by the classical VSM control. Hence, an …
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new technique of generation of convex polygon triangulation based on planted trivalent binary tree and ballot notation. The properties of the Catalan numbers were examined and their decomposition and application in developing the hierarchy and triangulation trees were analyzed. The method of storage and processing of triangulation was constructed on the basis of movements through the polygon. This method was derived from vertices and leaves of the planted trivalent binary tree. The research subject of the paper is analysis and comparison of a constructed method for solving of convex polygon triangulation problem with other methods and …
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The amount and variety of data generated through social media sites has increased along with the widespread use of social media sites. In addition, the data production rate has increased in the same way. The inclusion of personal information within these data makes it important to process the data and reach meaningful information within it. This process can be called intelligence and this meaningful information may be for commercial, academic, or security purposes. An example application is developed in this study for intelligence on Twitter. Crimes in Turkey are classified according to Turkish Statistical Institute criminal data and keywords are …
Identifying Criminal Organizations From Their Social Network Structures, Muhammet Serkan Çi̇nar, Burkay Genç, Hayri̇ Sever
Identifying Criminal Organizations From Their Social Network Structures, Muhammet Serkan Çi̇nar, Burkay Genç, Hayri̇ Sever
Turkish Journal of Electrical Engineering and Computer Sciences
Identification of criminal structures within very large social networks is an essential security feat. By identifying such structures, it may be possible to track, neutralize, and terminate the corresponding criminal organizations before they act. We evaluate the effectiveness of three different methods for classifying an unknown network as terrorist, cocaine, or noncriminal. We consider three methods for the identification of network types: evaluating common social network analysis metrics, modeling with a decision tree, and network motif frequency analysis. The empirical results show that these three methods can provide significant improvements in distinguishing all three network types. We show that these …
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
Turkish Journal of Electrical Engineering and Computer Sciences
Decimal floating point (DFP) number representation was proposed in IEEE-754-2008 in order to overcome binary floating point inaccuracy. Neglecting binary floating point verification has resulted in significant validity and economic losses. Formal verification can be a solution to similar DFP design problems. Verification techniques aiming at DFP are limited to functional methods whereas formal approaches have been neglected and traditional decision diagrams cannot model DFP representation complexity. In this paper, we propose an efficient canonical data structure that can model DFP properties. Our novel data structure models coefficient, exponent, sign, and bias of a DFP number. We will prove mathematically …
Detection Of Hemorrhage In Retinal Images Using Linear Classifiers And Iterative Thresholding Approaches Based On Firefly And Particle Swarm Optimization Algorithms, Kemal Adem, Mahmut Heki̇m, Seli̇m Demi̇r
Detection Of Hemorrhage In Retinal Images Using Linear Classifiers And Iterative Thresholding Approaches Based On Firefly And Particle Swarm Optimization Algorithms, Kemal Adem, Mahmut Heki̇m, Seli̇m Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
We propose a novel iterative thresholding approach based on firefly and particle swarm optimization to be used for the detection of hemorrhages, one of the signs of diabetic retinopathy disease. This approach consists of the enhancement of the image using basic preprocessing methods, the segmentation of vessels with the help of Gabor and Top-hat transformation for the removal of the vessels from the image, the determination of the number of regions with hemorrhages and pixel counts in these regions using firefly algorithm (FFA) and particle swarm optimization algorithm (PSOA)-based iterative thresholding, and the detection of hemorrhages with the help of …
Optimal Set Of Eeg Features In Infant Sleep Stage Classification, Maja Cic, Mario Milicevic, Igor Mazic
Optimal Set Of Eeg Features In Infant Sleep Stage Classification, Maja Cic, Mario Milicevic, Igor Mazic
Turkish Journal of Electrical Engineering and Computer Sciences
This paper evaluates six classification algorithms to assess the importance of individual EEG rhythms in the context of automatic classification of infant sleep. EEG features were obtained by Fourier transform and by a novel technique based on the empirical mode decomposition and generalized zero crossing method. Of six evaluated classification algorithms, the best classification results were obtained with the support vector machine for the combination of all presented features from four EEG channels. Three methods of attribute ranking were assessed: relief, principal component analysis, and wrapper-based optimized attribute weights. The outcomes revealed that the optimal selection of features requires one …
Improvement Of Quantized Adaptive Switching Median Filter For Impulse Noise Reduction In Gray-Scale Digital Images, Haidi Ibrahim, Ahmed Khaldoon Abdalameer
Improvement Of Quantized Adaptive Switching Median Filter For Impulse Noise Reduction In Gray-Scale Digital Images, Haidi Ibrahim, Ahmed Khaldoon Abdalameer
Turkish Journal of Electrical Engineering and Computer Sciences
Digital images may suffer from fixed value impulse noise due to several causes. The noise significantly degrades the quality of the image, which may affect the subsequence image processing. Therefore, a noise reduction technique is required to restore the image. In this paper, a new method, which is called improvement of quantized adaptive switching median filter (IQASMF), has been proposed to reduce the fixed value impulse noise from gray-scale digital images. The implementation of IQASMF has five processing blocks. The first processing block is the noise detection block, where the noise pixel candidates are detected based on the intensity value. …
Comparative Analysis Of A Novel Topology For Single-Phase Z-Source Inverter With Reduced Number Of Switches, Himanshu Sharma, Rintu Khanna, Neelu Jain
Comparative Analysis Of A Novel Topology For Single-Phase Z-Source Inverter With Reduced Number Of Switches, Himanshu Sharma, Rintu Khanna, Neelu Jain
Turkish Journal of Electrical Engineering and Computer Sciences
Z-source inverter has recently been introduced to overcome the limitations of conventional voltage source inverter. This paper deals with a novel topology of single-phase Z-source inverter (ZSI). This topology reduced the number of passive elements and active switches in order to make the inverter cheaper and smaller in size compared to traditional ZSI. Detailed analysis of the proposed topology is presented in this paper which includes calculations of boost factor, total harmonic disorder, magnitude of output voltage etc. Modulation technique used to control the switching of the proposed inverter is explained in detail. This paper also compares the proposed topology …
Neural Network Controller For Nanopositioning Of A Smooth Impact Drive Mechanism, Xiaohui Lu, Dong Chen, Tinghai Cheng, Zhe Li
Neural Network Controller For Nanopositioning Of A Smooth Impact Drive Mechanism, Xiaohui Lu, Dong Chen, Tinghai Cheng, Zhe Li
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, neural network theory is used to improve the positioning accuracy of smooth impact drive mechanisms (SIDMs), by designing a displacement controller that consists of a neural network identification (NNI) and a neural network controller (NNC). The dynamics of the SIDM are described by the NNI, which consists of an input layer, hidden layer, and output layer. The parameters of the NNI are adjusted using back propagation. The NNC is designed as a proportional-derivative (PD) controller, which is used to accurately control the displacement of the SIDM. The PD parameters are adjusted with an adaptive adjustment algorithm. A …
Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu
Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu
Turkish Journal of Electrical Engineering and Computer Sciences
Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …
A New Computer-Controlled Platform For Adc-Based True Random Number Generator And Its Applications, Selçuk Coşkun, İhsan Pehli̇van, Aki̇f Akgül, Bi̇lal Gürevi̇n
A New Computer-Controlled Platform For Adc-Based True Random Number Generator And Its Applications, Selçuk Coşkun, İhsan Pehli̇van, Aki̇f Akgül, Bi̇lal Gürevi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new …
Prey-Predator Algorithm For Discrete Problems: A Case For Examination Timetabling Problem, Surafel Luleseged Tilahun
Prey-Predator Algorithm For Discrete Problems: A Case For Examination Timetabling Problem, Surafel Luleseged Tilahun
Turkish Journal of Electrical Engineering and Computer Sciences
The prey-predator algorithm is a metaheuristic algorithm inspired by the interaction between a predator and its prey. Initial solutions are put into three categories: the better performing solution as the best prey, the worst performing solution as a predator, and the rest as ordinary prey. The best prey totally focuses on exploiting its neighborhood while the predator explores the search space searching for a promising region in the search space. The ordinary prey will be affected by these two extreme search behaviors of exploration and exploitation. The algorithm has been tested and found to be effective in solving different problems …
Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya
Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya
Turkish Journal of Electrical Engineering and Computer Sciences
Sleep electroencephalogram (EEG) signal is an important clinical tool for automatic sleep staging process. Sleep EEG signal is effected by artifacts and other biological signal sources, such as electrooculogram (EOG) and electromyogram (EMG), and since it is effected, its clinical utility reduces. Therefore, eliminating EOG artifacts from sleep EEG signal is a major challenge for automatic sleep staging. We have studied the effects of EOG signals on sleep EEG and tried to remove them from the EEG signals by using regression method. The EEG and EOG recordings of seven subjects were obtained from the Sleep Research Laboratory of Meram Medicine …
Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan
Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan
Turkish Journal of Electrical Engineering and Computer Sciences
Determining the category of a text document from its semantic content is highly motivated in the literature and it has been extensively studied in various applications. Also, the compact representation of the text is a fundamental step in achieving precise results for the applications and the studies are generously concentrated to improve its performance. In particular, the studies which exploit the aggregation of word-level representations are the mainstream techniques used in the problem. In this paper, we tackle text representation to achieve high performance in different text classification tasks. Throughout the paper, three critical contributions are presented. First, to encode …
A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci
A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci
Turkish Journal of Electrical Engineering and Computer Sciences
The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …
Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli
Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli
Turkish Journal of Electrical Engineering and Computer Sciences
Software development effort estimation is a critical activity of the project management process. In this study, machine learning algorithms were investigated in conjunction with feature transformation, feature selection, and parameter tuning techniques to estimate the development effort accurately and a new model was proposed as part of an expert system. We preferred the most general-purpose algorithms, applied parameter optimization technique (GridSearch), feature transformation techniques (binning and one-hot-encoding), and feature selection algorithm (principal component analysis). All the models were trained on the ISBSG datasets and implemented by using the scikit-learn package in the Python language. The proposed model uses a multilayer …
Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray
Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray
Turkish Journal of Electrical Engineering and Computer Sciences
In today's world, the internet of things (IoT) is developing rapidly. Wireless sensor network (WSN) as an infrastructure of IoT has limitations in the processing power, storage, and delay for data transfer to cloud. The large volume of generated data and their transmission between WSNs and cloud are serious challenges. Fog computing (FC) as an extension of cloud to the edge of the network reduces latency and traffic; thus, it is very useful in IoT applications such as healthcare applications, wearables, intelligent transportation systems, and smart cities. Resource allocation and task scheduling are the NP-hard issues in FC. Each application …
Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan
Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
In dynamic graphs, edge weights of the graph change with time and solving the shortest path problem in such graphs is an important real-world problem. The studies in the literature require excessive computational time for computing the dynamic shortest path since determining changing edge weights is difficult especially when the graph size becomes large. In this paper, we propose a dynamic bio-inspired algorithm for finding the dynamic shortest path for large graphs based on Physarum Solver, which is a shortest path algorithm for static graphs. The proposed method is evaluated using three different large graph models representing diverse real-life applications. …
Multiellipsoidal Extended Target Tracking With Known Extent Using Sequential Monte Carlo Framework, Süleyman Fati̇h Kara, Emre Özkan
Multiellipsoidal Extended Target Tracking With Known Extent Using Sequential Monte Carlo Framework, Süleyman Fati̇h Kara, Emre Özkan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we consider a variant of the extended target tracking (ETT) problem, namely the multiellipsoidal ETT problem. In multiellipsoidal ETT, target extent is represented by multiple ellipses, which correspond to the origin of the measurements on the target surface. The problem involves estimating the target's kinematic state and solving the association problem between the measurements and the ellipses. We cast the problem in a sequential Monte Carlo (SMC) framework and investigate different marginalization strategies to find an efficient particle filter. Under the known extent assumption, we define association variables to find the correct association between the measurements and …
Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang
Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, features extracted by convolutional neural networks (CNNs) are popularly used for image retrieval. In CNN representation, high-level features are usually chosen to represent the images in coarse-grained datasets, while mid-level features are successfully applied to describe the images for fine-grained datasets. In this paper, we combine these different levels of features as a joint feature to propose a robust representation that is suitable for both coarse-grained and fine-grained image retrieval datasets. In addition, in order to solve the problem that the efficiency of image retrieval is influenced by the dimensionality of indexing, a unified subspace learning model named spectral …
Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural
Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural
Turkish Journal of Electrical Engineering and Computer Sciences
Traditional machine learning algorithms assume that the training and test data have the same distribution, while this assumption does not necessarily hold in real applications. Domain adaptation methods take into account the deviations in data distribution. In this work, we study the problem of domain adaptation on graphs. We consider a source graph and a target graph constructed with samples drawn from data manifolds. We study the problem of estimating the unknown class labels on the target graph using the label information on the source graph and the similarity between the two graphs. We particularly focus on a setting where …
Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding
Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Temporal segmentation of facial expression sequences is important to understand and analyze human facial expressions. It is, however, challenging to deal with the complexity of facial muscle movements by finding a suitable metric to distinguish among different expressions and to deal with the uncontrolled environmental factors in the real world. This paper presents a two-step unsupervised segmentation method composed of rough segmentation and fine segmentation stages to compute the optimal segmentation positions in video sequences to facilitate the segmentation of different facial expressions. The proposed method performs localization of facial expression patches to aid in recognition and extraction of specific …
Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü
Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü
Turkish Journal of Electrical Engineering and Computer Sciences
Electrolyte current must be controlled in the water electrolysis systems. For this purpose, the power converter for the cell stack of the electrolyzer used in industrial hydrogen production is realized. A series resonant converter, which is suitable for high input voltage and low output current applications, is used as power stage of the electrolyzer. The high-frequency transformer is used for the impedance matching. While the system is running, the electrical resistance of the electrolyzer changes continuously; thus, fuzzy logic controller (FLC) is used to control the output current of the power converter. In this study, a 700-W converter prototype is …
High-Efficiency Design Of A Grid-Connected Pv Inverter Based On Interleaved Flyback Converter Topology, Bünyami̇n Tamyürek, Bi̇lgehan Kirimer
High-Efficiency Design Of A Grid-Connected Pv Inverter Based On Interleaved Flyback Converter Topology, Bünyami̇n Tamyürek, Bi̇lgehan Kirimer
Turkish Journal of Electrical Engineering and Computer Sciences
The importance of efficiency in photovoltaic (PV) inverter applications makes the topology selection as the critical first step. Due to the low efficiency concern, flyback converter is not the preferred topology in kilowatt range in spite of its galvanic isolation, low cost, and small size advantages. Therefore, the objective of this research is to change the perception in favor of flyback converter by designing a flyback-topology-based PV inverter at 2.5 kW with high efficiency. The enhancement in efficiency is achieved mainly by using silicon carbide switching devices, designing ultrahigh-efficiency flyback transformers with extremely low leakage inductance and by implementing a …
Channel Estimation For Ofdm-Im Systems, Yusuf Acar, Sultan Aldirmaz Çolak, Ertuğrul Başar
Channel Estimation For Ofdm-Im Systems, Yusuf Acar, Sultan Aldirmaz Çolak, Ertuğrul Başar
Turkish Journal of Electrical Engineering and Computer Sciences
Orthogonal frequency division multiplexing with index modulation (OFDM-IM) has been recently proposed to increase the spectral efficiency and improve the error performance of multicarrier communication systems. However, all the OFDM-IM systems assume that the perfect channel state information is available at the receiver. Nevertheless, channel estimation is a challenging problem in practical wireless communication systems for coherent detection at the receiver. In this paper, a novel method based on the pilot symbol-aided channel estimation technique is proposed and evaluated for OFDM-IM systems. Pilot symbols, which are placed equidistantly, allow the regeneration of the response of the channel so that pilot …
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …