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Full-Text Articles in Engineering

Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh Jan 2021

Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh

Turkish Journal of Electrical Engineering and Computer Sciences

A point-to-point (P2P) communication system based on the CPM-DSSS scheme ensures reliability, security, and antijamming capabilities. However, for reliable detection of data carrier synchronization of CPM-DSSS based system is one of the requirements. This paper presents a joint algorithm for carrier frequency offset (CFO) and carrier phase offset (CPO) estimation for CPM-DSSS based P2P system. The results indicate that the proposed CFO estimator is unbiased and can accurately estimate a wide range of offsets. Moreover, the proposed algorithm is compared with another research work. The results show that the proposed CFO and CPO estimation algorithm outperforms its counterpart with a …

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Advanced Single-Loop Discrete-Time Control For T-Type Voltage Source Inverterwith Minimum Capacitor Voltage Ripple Modulation, Manh Linh Nguyen, Phuong Vu Jan 2021

Advanced Single-Loop Discrete-Time Control For T-Type Voltage Source Inverterwith Minimum Capacitor Voltage Ripple Modulation, Manh Linh Nguyen, Phuong Vu

Turkish Journal of Electrical Engineering and Computer Sciences

This research focuses on improving the performance of the voltage source inverter (VSI), which has been widely used in practical applications such as uninterruptible power supply (UPS), photovoltaic (PV) systems in standalone mode. To reduce the total harmonic distortion (THD) of the output voltage without increasing the switching frequency, the T-type three levels inverter with enhanced modulation strategy, which minimizes the voltage ripple of the two input capacitors, is employed. In addition, a new single-loop fully digital control strategy in which various advanced control techniques such as proportional-integral observer, one-step ahead minimum prediction error, and model-based current command generator is …

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An Integrated Optimal Method For Cloud Service Ranking, Mohammad Hossein Nejat, Homayun Motameni, Hamed Vahdat-Nejad Jan 2021

An Integrated Optimal Method For Cloud Service Ranking, Mohammad Hossein Nejat, Homayun Motameni, Hamed Vahdat-Nejad

Turkish Journal of Electrical Engineering and Computer Sciences

Many cloud providers present various services with different attributes. It is a complex, lengthy process to select a cloud service that meets user requirements from an assortment of services. At the same time, user requirements are sometimes defined with imprecision (sets or intervals), whereas it is also important to consider the quality of user feedback (QoU) and quality of service (QoS) attributes for ranking. Besides, each MADM method has a di erent procedure, which causes functional contradictions. These contradictions have led to confusion in choosing the best MADM method. It is necessary to provide a method that harmonizes the results. …

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Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant Jan 2021

Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we introduce a new deep-learning-based system that can compose structured Turkish makam music (TMM) in the symbolic domain. Presented artificial TMM composer (ATMMC) takes eight initial notes from a human user and completes the rest of the piece. The backbone of the composer system consists of multilayered long short-term memory (LSTM) networks. ATMMC can create pieces in Hicaz and Nihavent makams in Şarkı form, which can be viewed and played with Mus2, a notation software for microtonal music. Statistical analysis shows that pieces composed by ATMMC are approximately 84% similar to training data. ATMMC is an open-source …

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Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification, Bakshi Rohit Prasad, Sonali Agarwal Jan 2021

Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification, Bakshi Rohit Prasad, Sonali Agarwal

Turkish Journal of Electrical Engineering and Computer Sciences

Machine learning (ML) on Big Data has gone beyond the capacity of traditional machines and technologies. ML for large scale datasets is the current focus of researchers. Most of the ML algorithms primarily suffer from memory constraints, complex computation, and scalability issues.The least square twin support vector machine (LSTSVM) technique is an extended version of support vector machine (SVM). It is much faster as compared to SVM and is widely used for classification tasks. However, when applied to large scale datasets having millions or billions of samples and/or large number of classes, it causes computational and storage bottlenecks. This paper …

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Evaluation Of Cable And Busbar System In Multiconductor Distribution Systems Interms Of Current And Magnetic Field Distributions, Yunus Berat Demi̇rol, Mehmet Aytaç Çinar, Bora Alboyaci Jan 2021

Evaluation Of Cable And Busbar System In Multiconductor Distribution Systems Interms Of Current And Magnetic Field Distributions, Yunus Berat Demi̇rol, Mehmet Aytaç Çinar, Bora Alboyaci

Turkish Journal of Electrical Engineering and Computer Sciences

The selection of power distribution components is of great importance in electrical facilities. Cable and busbar systems are widely used applications, such as electric vehicle charge stations, microgrids and energy storage systems, for power distribution in the distribution grid. In this study, the current distribution on the parallel conductors and magnetic field distributions around cable and busbar structures is evaluated for studied application where the power is distributed using a cable system between a converter transformer and a converter. All modeling and analyzes are conducted using ANSYS Electronics Suite software, by applying balanced and pure sinusoidal current excitation. Obtained results …

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Presentation Attack Detection For Face Recognition Using Remotephotoplethysmography And Cascaded Fusion, Mehmet Fati̇h Gündoğar, Çi̇ğdem Eroğlu Erdem Jan 2021

Presentation Attack Detection For Face Recognition Using Remotephotoplethysmography And Cascaded Fusion, Mehmet Fati̇h Gündoğar, Çi̇ğdem Eroğlu Erdem

Turkish Journal of Electrical Engineering and Computer Sciences

Spoofing (presentation) attacks are important threats for face recognition and authentication systems, which try to deceive them by presenting an image or video of a different subject, or by using a 3D mask. Remote (non-contact) photoplethysmography (rPPG) is useful for liveness detection using a facial video by estimating the heart-rate of the subject. In this paper, we first compare the presentation attack detection performance of three different rPPG-based heart rate estimation methods on four datasets (3DMAD, Replay-Attack, Replay-Mobile, and MSU-MFSD). We also present a cascaded fusion system, which utilizes a multistage ensemble of classifiers using rPPG, motion-based (including head-pose, eye-gaze …

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Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler Jan 2021

Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler

Turkish Journal of Electrical Engineering and Computer Sciences

The question of whether opinions of stubborn agents result in Nash equilibrium under the presence of troll is investigated in this study. The opinion dynamics is modelled as a differential game played by n agents during a finite time horizon. Two types of agents, ordinary agents and troll, are considered in this game. Troll is treated as a malicious stubborn content maker who disagrees with every other agent. On the other hand, ordinary agents maintain cooperative communication with other ordinary agents and they disagree with the troll. Under this scenario, explicit expressions of opinion trajectories are obtained by applying Pontryagin?s …

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A Hybrid Approach Based On Transfer And Ensemble Learning For Improvingperformances Of Deep Learning Models On Small Datasets, Tunç Gülteki̇n, Aybars Uğur Jan 2021

A Hybrid Approach Based On Transfer And Ensemble Learning For Improvingperformances Of Deep Learning Models On Small Datasets, Tunç Gülteki̇n, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

The need for high-volume data is one of the challenging requirements of the deep learning methods, and it makes it harder to apply deep learning algorithms to domains in which the data sources are limited, in other words, small. These domains may vary from medical diagnosis to satellite imaging. The performances of the deep learning methods on small datasets can be improved by the approaches such as data augmentation, ensembling, and transfer learning. In this study, we propose a new approach that utilizes transfer learning and ensemble methods to increase the accuracy rates of convolutional neural networks for classification tasks …

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Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd Jan 2021

Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd

Turkish Journal of Electrical Engineering and Computer Sciences

Skin cancer is one of the most common cancers worldwide caused by excessive development of skin cells. Considering the rapid growth of the use of deep learning algorithms for skin cancer detection, selecting the optimal algorithm has become crucial to determining the efficiency of computer-aided diagnosis (CAD) systems developed for the healthcare sector. However, a sufficient number of criteria and parameters must be considered when selecting an ideal deep learning algorithm. A generally accepted method for benchmarking deep learning models for skin cancer classification is unavailable in the current literature. This paper presents a multi-criteria decision-making framework for evaluating and …

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Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇ Jan 2021

Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇

Turkish Journal of Electrical Engineering and Computer Sciences

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common method used in brain imaging to study neurological disorders. Diagnosis of neurological disorders such as ALS, Parkinson's, attention deficit hyperactivity disorder is important in biomedical studies. In recent years, deep learning (DL) models have been started to be applied in the literature for the diagnosis of these diseases. In this study, event-related potentials (ERPs) were obtained from EEG signals obtained as a …

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Diagnosis Of Paroxysmal Atrial Fibrillation From Thirty-Minute Heart Ratevariability Data Using Convolutional Neural Networks, Murat Sürücü, Yalçin İşler, Resul Kara Jan 2021

Diagnosis Of Paroxysmal Atrial Fibrillation From Thirty-Minute Heart Ratevariability Data Using Convolutional Neural Networks, Murat Sürücü, Yalçin İşler, Resul Kara

Turkish Journal of Electrical Engineering and Computer Sciences

Paroxysmal atrial fibrillation (PAF) is the initial stage of atrial fibrillation, one of the most common arrhythmia types. PAF worsens with time and affects the patient?s life quality negatively. In this study, we aimed to diagnose PAF early, so patients can start taking precautions before this disease gets worse. We used the atrial fibrillation prediction database, an open data from Physionet and constructed our approach using convolutional neural networks. Heart rate variability (HRV) features are calculated from time-domain measures, frequency-domain measures using power spectral density estimations (fast Fourier transform, Lomb-Scargle, and Welch periodogram), time-frequencydomain measures using wavelet transform, and nonlinear …

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A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran Jan 2021

A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper investigates a multiple sensor fusion based drift compensation technique for a mecanum wheeledmobile robot platform. The mobile robot is equipped with high-precision encoders integrated to the wheels and fouraccelerometers placed on its chassis. The proposed algorithm combines the information from the encoders and theacceleration sensors to estimate the total drift in the acceleration dimension. The inner loop controller is designedutilizing a disturbance-observer-based acceleration control structure which is blind against the slipping motion of thewheels. The estimated drift acceleration from the sensor fusion is then mapped back to the joint space of the robot andused as additional compensation over …

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A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün Jan 2021

A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün

Turkish Journal of Electrical Engineering and Computer Sciences

A hybrid numerical model is presented for solving long range electromagnetic wave propagation problems involving objects on or above the ground surface by hybridizing the two-way split-step parabolic equation (2W-SSPE) method with the method of moments (MoM). The advantages of the proposed model are twofold: (i) It reduces the staircasing error in irregular terrain modeling, which usually occurs when the standard SSPE method is used alone. This is achieved by employing the MoM to more accurately obtain the scattered fields from slanted/curved surfaces. (ii) It enables the SSPE method to handle the problems involving objects above the Earth's surface, which …

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A Zugunruhe Data Collection System Using Passive Infrared Sensors, Ryan Terry, Luis E. Ramirez, Carol Carrera, Abigail Kimmitt, Kira Delmore, Ana Goulart Jan 2021

A Zugunruhe Data Collection System Using Passive Infrared Sensors, Ryan Terry, Luis E. Ramirez, Carol Carrera, Abigail Kimmitt, Kira Delmore, Ana Goulart

Pursue: Undergraduate Research Journal

When engineers and biologists work together, there is a lot to learn on both sides. For instance, our work introduced us to zugunruhe, which is a German word that means “unrest”. It is used in the context of migratory birds, as they become restless at night, inside their cages, during their migratory period. When does zugunruhe start? It usually starts when the weather becomes cold and the days shorter, but it varies for different bird species. Moreover, global warming has caused changes in zungunruhe’s timing, which made it even harder to predict. Another question is about genetics: is …

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Interferometry In Fmcw Radars, Assid Nait, Theodore Grosch Jan 2021

Interferometry In Fmcw Radars, Assid Nait, Theodore Grosch

The Kennesaw Journal of Undergraduate Research

interferometry is used in many fields using all frequencies of the electromagnetic spectrum and sound waves. In this study, data was collected from an FMCW radar is used at multiple heights above a flat surface on which sat a single retroreflector. These data were post-processed to discover the signal obtained from the target and then the phase form the radar at multiple locations was compared. Using the known geometry and measured phase, we find the interferometry is possible using a freerunning radar under certain geometric conditions.

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Wireless Sensing - Enabler Of Future Wireless Technologies, Hali̇se Türkmen, Muhammad Sohai̇b J. Solai̇ja, Armed Tusha, Hüseyi̇n Arslan Jan 2021

Wireless Sensing - Enabler Of Future Wireless Technologies, Hali̇se Türkmen, Muhammad Sohai̇b J. Solai̇ja, Armed Tusha, Hüseyi̇n Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Withthe completion of the 5G standardization efforts, the wireless communication world has now turned tothe road ahead, the future wireless communication visions. One common vision is that future networks will be flexible,or able to accommodate an even richer variety of services with stringent, often conflicting requirements. This ambitiousfeat can only be accomplished with a ubiquitous awareness of the radio and physical environment. To this end, thispaper highlights the importance of wireless sensing as a means for radio environment awareness and surveys wirelesssensing methods under different domains. Then, a review of wireless sensing from a standardization perspective is given.These standardization efforts …

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A Novel Method For Soc Estimation Of Li-Ion Batteries Using A Hybrid Machinelearning Technique, Eymen İpek, Murat Yilmaz Jan 2021

A Novel Method For Soc Estimation Of Li-Ion Batteries Using A Hybrid Machinelearning Technique, Eymen İpek, Murat Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

The battery system is one of the key components of electric vehicles (EV) which has brought groundbreaking technologies. Since modern EVs have mostly Li-ion batteries, they need to be monitored and controlled to achieve safe and high-performance operation. Particularly, the battery management system (BMS) uses complex processing systems that perform measurements, estimation of the battery states, and protection of the system. State of charge (SOC) estimation is a major part of these processes which defines remaining capacity in the battery until the next charging operation as a proportion to the total battery capacity. Since SOC is not a parameter that …

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Comparison Of Risc-V And Transport Triggered Architectures For A Postquantumcryptography Application, Lati̇f Akçay, Siddika Berna Örs Yalçin Jan 2021

Comparison Of Risc-V And Transport Triggered Architectures For A Postquantumcryptography Application, Lati̇f Akçay, Siddika Berna Örs Yalçin

Turkish Journal of Electrical Engineering and Computer Sciences

Cryptography is one of the basic phenomena of security systems. However, some of the widely used publickey cryptography algorithms can be broken by using quantum computers. Therefore, many postquantum cryptography algorithms are proposed in recent years to handle this issue. NTRU (Nth degree truncated polynomial ring units) is one of the most important of these quantum-safe algorithms. Besides the importance of cryptography algorithms, the architecture where they are implemented is also essential. In this study, we developed an NTRU public key cryptosystem application and designed several processors to compare them in many aspects. We address two different architectures in this …

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Development Of An Intelligent Controller For Robot-Aided Assessment Andtreatment Guidance In Physical Medicine And Rehabilitation, Mehmet Emi̇n Aktan, Erhan Akdoğan Jan 2021

Development Of An Intelligent Controller For Robot-Aided Assessment Andtreatment Guidance In Physical Medicine And Rehabilitation, Mehmet Emi̇n Aktan, Erhan Akdoğan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, an intelligent controller was developed for a rehabilitation robot called DIAGNOBOT, which can be used for assessment and treatment in the rehabilitation of wrist and forearm. The controller has a decision support system structure strengthened with conventional statistical methods and databases. The controller uses the patient's biomechanical parameters to make an assessment and proposes a treatment in line with this. In accordance with the recommended treatment, it produces the control parameters, torque, and position information for the control of the rehabilitation robot. The system's ability of assessment and treatment was tested with voluntary patients. Through these test …

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Ensemble Learning Of Multiview Cnn Models For Survival Time Prediction Of Braintumor Patients Using Multimodal Mri Scans, Abdela Ahmed Mossa, Ulus Çevi̇k Jan 2021

Ensemble Learning Of Multiview Cnn Models For Survival Time Prediction Of Braintumor Patients Using Multimodal Mri Scans, Abdela Ahmed Mossa, Ulus Çevi̇k

Turkish Journal of Electrical Engineering and Computer Sciences

Brain tumors have been one of the most common life-threatening diseases for all mankind. There have beenhuge efforts dedicated to the development of medical imaging techniques and radiomics to diagnose tumor patients quicklyand e?iciently. One of the main aims is to ensure that preoperative overall survival time (OS) prediction is accurate.Recently, deep learning (DL) algorithms, and particularly convolutional neural networks (CNNs) achieved promisingperformances in almost all computer vision fields. CNNs demand large training datasets and high computational costs.However, curating large annotated medical datasets are difficult and resource-intensive. The performances of singlelearners are also unsatisfactory for small datasets. Thus, this study …

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Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks, Mevlüt Ersoy, Beki̇r Aksoy Jan 2021

Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks, Mevlüt Ersoy, Beki̇r Aksoy

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor network (WSN) systems are frequently used today as a result of rapid technological developments. Wireless sensor networks, which form the basis of the Internet of Things (IoT), have a wide range of use in theworld from education to health, and from military applications to home applications. It enables the data obtained fromthe sensors to be transferred between nodes with the help of end-to-end wireless protocols. In parallel with the increasingnumber of nodes in WSN, data tra?ic density also increases. Due to the limitations of the WSN network, lost packetrates also increase with increasing data tra?ic. In this study, …

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Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms, Hasan Raza, Ghalib Hussain, Noor Khan Jan 2021

Low Communication Parallel Distributed Adaptive Signal Processing (Lc-Pdasp)Architecture For Processing-Inefficient Platforms, Hasan Raza, Ghalib Hussain, Noor Khan

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a low communication parallel distributed adaptive signal processing (LC-PDASP) architecturefor a group of computationally incapable and inexpensive small platforms is introduced. The proposed architectureis capable of running computationally high adaptive filtering algorithms parallely with minimally low communicationoverhead. A recursive least square (RLS) adaptive algorithm based on the application of multiple-input multiple-output(MIMO) channel estimation is implemented on the proposed LC-PDASP architecture. Complexity and Communicationburden of proposed LC-PDASP architecture are compared with that of conventional PDASP architecture. The compar-ative analysis shows that the proposed LC-PDASP architecture exhibits low computational complexity and provides animprovement more than of85%reduced communication burden than …

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Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie Jan 2021

Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie

Turkish Journal of Electrical Engineering and Computer Sciences

The most challenging objective in machine translation of sign language has been the machine?s inability tolearn interoccluding finger movements during an action process. This work addresses the problem of teaching a deeplearning model to recognize differently oriented skeletal data. The multi-view 2D skeletal sign language video data isobtained using 3D motion-captured system. A total of 9 signer views were used for training the proposed network andthe 6 for testing and validation. In order to obtain multi-view deep features for recognition, we proposed an end-to-endtrainable multistream convolutional neural network (CNN) with late feature fusion. The fused multiview features arethen inputted to …

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Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat Jan 2021

Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat

Turkish Journal of Electrical Engineering and Computer Sciences

Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …

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Impact Of Hybrid Power Generation On Voltage, Losses, And Electricity Cost Indistribution Networks, Yavuz Ateş, Tayfur Gökçek, Ahmet Yi̇ği̇t Arabul Jan 2021

Impact Of Hybrid Power Generation On Voltage, Losses, And Electricity Cost Indistribution Networks, Yavuz Ateş, Tayfur Gökçek, Ahmet Yi̇ği̇t Arabul

Turkish Journal of Electrical Engineering and Computer Sciences

Energy and its capacity has emerged as one of the biggest distribution challenges all over the world. The existing grid becomes insufficient along with the expansion of the consumption. Therefore, the number of distributed generation (DG) in distribution networks increases and it allows us to sell back the extra energy. However, the efficiency of energy must be maintained into optimal values from the grid to the end-users. In spite of a lot of advantages of DG units, there are some disadvantages like fluctuations in voltage, increments of power losses, wrong protection coordination, harmonic and energy quality issues etc.. If the …

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Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut Jan 2021

Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that …

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Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid Jan 2021

Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid

Turkish Journal of Electrical Engineering and Computer Sciences

The inclusion of renewable energy sources in a distribution system to form a dispersed or decentralized generation network has gained tremendous progress in recent years. The architecture of the distribution system has the potential to serve as a microgrid during an islanding operation connected directly to the load center while excited fully by renewable technologies. This paper deals with planning and designing of a medium voltage power distribution system in a rural area of Pakistan affluent with abundant reserves of renewable sources of electricity. Two types of distribution system architectures, namely radial and ring systems, are simulated using a power …

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Fpga Implementation Of Lsd-Omp For Real-Time Ecg Signal Reconstruction, Önder Polat, Sema Kayhan Jan 2021

Fpga Implementation Of Lsd-Omp For Real-Time Ecg Signal Reconstruction, Önder Polat, Sema Kayhan

Turkish Journal of Electrical Engineering and Computer Sciences

Compressed sensing is widely used to compress electrocardiogram (ECG) signals, but the major challenges of the compressed sensing algorithms are their highly complex signal reconstruction processes. In this paper, a reconfigurable high-speed and low-power field-programmable gate array (FPGA) implementation of the least support denoising-orthogonal matching pursuit (LSD-OMP) algorithm for the real-time reconstruction of the ECG signals is presented. The contribution of this study is two-fold: Firstly, LSD-OMP can pick more than one element at each iteration and reconstruct the sparse signal using less number of iterations as compared to the standard OMP algorithms. Latency of the proposed design is therefore …

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Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman Jan 2021

Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

We present a bagging ensemble of convolutional networks in combination with the test-time augmentation technique to improve performance on the cross-dataset gender recognition problem. The bagging ensemble combines the predictions from multiple homogeneous models into the ensemble prediction. Augmentation techniques are often used in the learning phase of the CNNs to improve the generalization ability. On the other hand, test-time augmentation is not a common method used in the testing phase of the learned model. We conducted experiments on models trained using different hyperparameters. We augmented the test data and combine the predictive outputs from these network models. Experiments performed …

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