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Articles 631 - 660 of 3106
Full-Text Articles in Engineering
A Novel S-Box-Based Postprocessing Method For True Random Number Generation, Erdi̇nç Avaroğlu, Taner Tuncer
A Novel S-Box-Based Postprocessing Method For True Random Number Generation, Erdi̇nç Avaroğlu, Taner Tuncer
Turkish Journal of Electrical Engineering and Computer Sciences
The quality of randomness in numbers generated by true random number generators (TRNGs) depends on the source of entropy. However, in TRNGs, sources of entropy are affected by environmental changes and this creates a correlation between the generated bit sequences. Postprocessing is required to remove the problem created by this correlation in TRNGs. In this study, an S-box-based postprocessing structure is proposed as an alternative to the postprocessing structures seen in the published literature. A ring oscillator (RO)-based TRNG is used to demonstrate the use of an S-box for postprocessing and the removal of correlations between number sequences. The statistical …
Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari
Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari
Turkish Journal of Electrical Engineering and Computer Sciences
Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, …
Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen
Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen
Turkish Journal of Electrical Engineering and Computer Sciences
Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, and very severe stages. Diagnosis of COPD at early stages needs additional clinical tests for even experienced specialists. The study aims at detecting the severity of the COPD to start treatment for preventing the progression of the disease to the next levels. We analyzed 12-channel lung sounds with different COPD severities from RespiratoryDatabase@TR. The lung sounds were recorded from the clinical auscultation points from 41 patients on …
A New Configuration For Four-Switch Three-Phase Inverters Based On A Switched-Capacitor Step-Up Cell For Electric Vehicles Application, Alireza Lahooti Eshkevari, Ali Mosallanejad, Mohammad Sadegh Sepasian
A New Configuration For Four-Switch Three-Phase Inverters Based On A Switched-Capacitor Step-Up Cell For Electric Vehicles Application, Alireza Lahooti Eshkevari, Ali Mosallanejad, Mohammad Sadegh Sepasian
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new configuration for four-switch three-phase inverters based on a step-up switchedcapacitor cell, which is called switched-capacitor four-switch three-phase inverter (SCFSTPI). This converter includes eight power switches and two DC-link capacitors. Voltage step-up feature, high efficiency, integrated structure, and bidirectional power flow are the main contribution of this new configuration. A modified space vector modulation (SVM) strategy is presented to generate appropriate pulses for the converter. This modulation method also eliminates the effect of capacitors voltage imbalance problem on the inverter output voltage and current. Simulation and experimental results are presented and investigated to confirm the performance …
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …
Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang
Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang
Turkish Journal of Electrical Engineering and Computer Sciences
Wind turbine (WT) arrays in wind farms can cause serious interference on nearby radar stations. This interference could be filtered out if wind turbine radar echo (WTRE) can be obtained accurately. Considering the singleness of in-field experiments, numerical simulation became the majority among such works, but few of them reached necessary accuracy. Therefore, we propose a solution method of WTRE based on three-dimensional (3-D) scattering point model. Firstly, we use the nonuniform rational B-spline to build the 3-D model of WT. Secondly, based on the method of moments (MoM), the Rao-Wilton-Gisson (RWG) basis function is adopted to discretize the integral …
Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala
Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala
Turkish Journal of Electrical Engineering and Computer Sciences
Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, apple images taken with near-infrared (NIR) cameras were classified as bruised and healthy objects using iterative thresholding approaches based on artificial bee colony (ABC) and particle swarm optimization (PSO) algorithms supported by a convolutional neural network (CNN) deep learning model. The proposed model includes the following stages: image acquisition, image preprocessing, the segmentation of anatomical regions (stem-calyx regions) to be discarded, the detection of bruised areas on the apple images, and their classification. For this aim, by using the image acquisition platform with a NIR camera, a total of 1200 images at 6 different angles were taken …
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati
Turkish Journal of Electrical Engineering and Computer Sciences
In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
Turkish Journal of Electrical Engineering and Computer Sciences
Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban
Turkish Journal of Electrical Engineering and Computer Sciences
Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …
Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇
Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇
Turkish Journal of Electrical Engineering and Computer Sciences
A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan?Äôs first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling …
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …
Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli
Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli
Turkish Journal of Electrical Engineering and Computer Sciences
Energy management is an emerging problem nowadays and utilization of renewable energy sources is an efficient solution. Solar radiation is an important source for electricity generation. For effective utilization, it is important to know precisely the amount from different sources and at different horizons: minutes, hours, and days. Depending on the horizon, two main classes of methods can be used to forecast the solar radiation: statistical time series forecasting methods for short to midterm horizons and numerical weather prediction methods for medium- to long-term horizons. Although statistical time series forecasting methods are utilized in the literature, there are a limited …
An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran
An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran
Turkish Journal of Electrical Engineering and Computer Sciences
The majority of the state-of-the-art text categorization algorithms are supervised and therefore require prior training. Besides the rigor involved in developing training datasets and the requirement for repetition of training for different texts, working with multilingual texts poses additional unique challenges. One of these challenges is that the developer is required to have many different languages involved. Term expansion such as query expansion has been applied in numerous applications; however, a major drawback of most of these applications is that the actual meaning of terms is not usually taken into consideration. Considering the semantics of terms is necessary because of …
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …
Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul
Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul
Turkish Journal of Electrical Engineering and Computer Sciences
Classification of a synthetic aperture radar (SAR) image is an essential process for SAR image analysis and interpretation. Recent advances in imaging technologies have allowed data sizes to grow, and a large number of applications in many areas have been generated. However, analysis of high-resolution SAR images, such as classification, is a time-consuming process and high-speed algorithms are needed. In this study, classification of high-speed denoised SAR image patches by using Apache Spark clustering framework is presented. Spark is preferred due to its powerful open-source cluster-computing framework with fast, easy-to-use, and in-memory analytics. Classification of SAR images is realized on …
Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz
Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz
Turkish Journal of Electrical Engineering and Computer Sciences
n this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similar to a convolutional layer of a neural network, the normalized-cross-correlational (NCC) layer, which we utilize for designing a target detection/recognition filter bank, is proposed. By employing the NCC layer in a neural network structure, we introduce a framework, in which supervised training is used to calculate the optimal filter shape and the optimum number of filters required for a specific target detection/recognition task on infrared images. We also propose the mean-absolute-deviation NCC (MAD-NCC) layer, an efficient implementation …
Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K
Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K
Turkish Journal of Electrical Engineering and Computer Sciences
The main aim of this paper is to introduce a new approach to enhance speech signals by exploring the advantages of nonlocal means (NLM) estimation and empirical mode decomposition. NLM, a patch-based denoising method, is extensively used for two-dimensional signals like images. However, its use for one-dimensional signals has been attracting more attention recently. The NLM-based approach is quite useful for removing low-frequency noises based on nonlocal similarities present among samples of the signal. However, there is an issue of under averaging in the high-frequency regions. The temporal and spectral characteristics of the speech signal are changing markedly over time. …
A Symmetric-Based Framework For Securing Cloud Data At Rest, Mohammed Mohammed, Fadhil Abed
A Symmetric-Based Framework For Securing Cloud Data At Rest, Mohammed Mohammed, Fadhil Abed
Turkish Journal of Electrical Engineering and Computer Sciences
Cloud computing is the umbrella term for delivering services via the Internet. It enables enterprises and individuals to access services such as virtual machines, storage, or applications on demand. It allows them to achieve more by paying less, and it removes the barrier of installing physical infrastructure. However, due to its openness and availability over the Internet, the issue of ensuring security and privacy arises. This requires careful consideration from enterprises and individuals before the adoption of cloud computing. In order to overcome security issues, cloud service providers are required to use strong security measures to secure their storage and …
On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz
On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
In this article, we provide further asymptotic analysis to the higher-order statistics (HOS) of the channel capacity over generalized fading channels, especially by proposing simple and closed-form expressions each of which can be easily computed as a tight bound revealing the existence of constant gap between the actual and asymptotic HOS of the channel capacity in the limit of both high and low signal-to-noise ratios. As such, we show that these closed-form asymptotic expressions are insightful enough to comprehend the diversity gains. The mathematical formalism we followed in this article is illustrated with some selected numerical examples that validate the …
Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim
Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
It is of great interest for Mobile Network Operators (MNOs) to know how well their network infrastructure performance behaves in different geographical regions of their operating country compared to their horizontal competitors. However, traditional network monitoring and measurement methods of network infrastructure use limited numbers of measurement points that are insufficient for detailed analysis and expensive to scale using an internal workforce. On the other hand, the abundance of crowdsourced content can engender various unforeseen opportunities for MNOs to cope with this scaling problem. This paper investigates end-to-end reliability and packet loss (PL) performance comparisons of MNOs using a previously …
A Compact Wideband Series Linear Dielectric Resonator Array Antenna, Yazeed Qasayneh, Abdullulah Almuhaisen, Talha Yazdani
A Compact Wideband Series Linear Dielectric Resonator Array Antenna, Yazeed Qasayneh, Abdullulah Almuhaisen, Talha Yazdani
Turkish Journal of Electrical Engineering and Computer Sciences
This communication presents a miniaturised series linear wideband array of notched rectangular dielectric resonator antennas that operate in the band IEEE 802.11a. Three dielectric resonators (DRs) were excited through the aperture slots coupled with a microstrip feed. To improve the array gain, the aperture slots were placed based on the attributes related to the standing-wave ratio on a short-ended microstrip feeder to obtain optimal joint power for the DRs, while the bandwidth was improved using the notched rectangular DRs. An equivalent impedance model of the proposed array was postulated to provide physical insight into the array resonance behaviour. The impedance …
Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh
Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh
Turkish Journal of Electrical Engineering and Computer Sciences
An eight-port X-band power splitter based on binary Wilkinson power splitter topology is presented in this paper. The proposed power splitter consists of three stages, with one, two, and four equal power splitters in the first, second, and third stages, respectively. The input power is divided equally between the eight outputs to provide an equal-split power splitter. Evaluation of the structure is carried out using even- and odd-mode techniques. An epoxy laminate FR4 substrate with thickness of 0.5 mm is chosen, while the designed power splitter is simulated using Keysight Advanced Design System 2019 and ANSYS High Frequency Structure Simulation. …
Sensor Anomaly Detection In The Industrial Internet Of Things Based On Edge Computing, Dequan Kong, Desheng Liu, Lei Zhang, Lili He, Qingwu Shi, Xiaojun Ma
Sensor Anomaly Detection In The Industrial Internet Of Things Based On Edge Computing, Dequan Kong, Desheng Liu, Lei Zhang, Lili He, Qingwu Shi, Xiaojun Ma
Turkish Journal of Electrical Engineering and Computer Sciences
In the industrial internet of things (IIoT), because thousands of pieces of hardware, instruments, and various controllers are involved, the core problem is the sensors. Detection using sensors is the bottom line of the IIoT, directly affecting the detection accuracy and control indicators of the IIoT system. However, when a large number of real-time data generated by IIoT devices are transferred to cloud computing centers, large-scale data will inevitably bring computing load, which will affect the computing speed of cloud computing centers and increase the computing load of cloud computing data centers. These factors directly lead to instability and delay …
A Wide Angle Multiple Beam Lens For Convex Conformal Arrays, Rasi̇me Uyguroglu, Abdullah Y. Oztoprak
A Wide Angle Multiple Beam Lens For Convex Conformal Arrays, Rasi̇me Uyguroglu, Abdullah Y. Oztoprak
Turkish Journal of Electrical Engineering and Computer Sciences
Multifocal lenses have been widely used as multiple beam forming networks for linear and planar arrays, but are not suitable for large convex conformal arrays as they are not physically realizable for wide angle beams. In this study, a new lens design especially suitable for convex conformal arrays is introduced. The new lens has no perfect focal points, but there are a certain number of correct phases in each of the beam directions. The directional patterns of the radiating elements are also taken into account to improve radiation patterns for desired directions. It has been shown that the new lens …
Rms Frequency Error Performance And Spurious Signals In Two-Point Modulators Due To Path Imbalances, Gökhun Selçuk, Kaan Üçel
Rms Frequency Error Performance And Spurious Signals In Two-Point Modulators Due To Path Imbalances, Gökhun Selçuk, Kaan Üçel
Turkish Journal of Electrical Engineering and Computer Sciences
In this study the authors introduce an analysis of rms frequency error performance and spurious signals generated by two-point modulators. The analysis is not limited to a constant delay and magnitude imbalance between modulation paths but allows frequency-dependent group delay and amplitude variations as well. Moreover, a discrete time phase frequency detector model is incorporated in Laplace domain analysis that takes into account the sampling nature of a phase-locked loop (PLL). Using the spectrum of pulse width modulated charge pump pulses, the spurious signals at the output of the PLL are evaluated. The proposed formulae are tested on a practical …
Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani
Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a Wilkinson power divider (WPD) is presented with ultrawide-band operation and harmonic suppression. This WPD is designed using coupling lines and meandered open stubs at main branches. The center frequency of the presented WPD is 4.25 GHz, which is fabricated and measured on RT/Duroid substrate with dielectric constant of 2.2. The proposed WPD provides good filtering band with high attenuation level. The 15 dB return loss operational bandwidth (BW) of the WPD is obtained between 3.2 GHz and 5.3 GHz, which shows 50 % operational bandwidth.
Operation Scheme For Mmc-Based Statcom Using Modified Instantaneous Symmetrical Components, Qing Duan, Wanxing Sheng, Guanglin Sha, Zhen Li, Caihong Zhao, Penghua Li, Chunyan Ma
Operation Scheme For Mmc-Based Statcom Using Modified Instantaneous Symmetrical Components, Qing Duan, Wanxing Sheng, Guanglin Sha, Zhen Li, Caihong Zhao, Penghua Li, Chunyan Ma
Turkish Journal of Electrical Engineering and Computer Sciences
Modular multilevel converters (MMCs) are characterized by modularization and multielectric equality, and the application of this structure to a high-voltage large-capacity static synchronous compensator (STATCOM) shows good potential. In this paper, a modified instantaneous symmetrical component method is proposed for positive- and negative-sequence decomposition, i.e. the critical part of the control device, which can accurately detect the instantaneous value of each sequence component in three-phase asymmetrical phasors in real time. Then, based on this method, the paper proposes a control method for MMC-based STATCOMs that solves the problems of multi-DC (direct current) voltage balance, grid-connected current control, and circulation suppression. …