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- Deep learning (67)
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Articles 541 - 570 of 3106
Full-Text Articles in Physical Sciences and Mathematics
Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang
Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang
Turkish Journal of Electrical Engineering and Computer Sciences
This study develops the deep Q-network (DQN)-based noise suppression for robust speech recognition purposes under ambient noise. We thus design a reinforcement algorithm that combines DQN training with a deep neural networks (DNN) to let reinforcement learning (RL) work for complex and high dimensional environments like speech recognition. For this, we elaborate on the DQN training to choose the best action that is the quantized noise suppression gain by the observation of noisy speech signal with the rewards of DQN including both the word error rate (WER) and objective speech quality measure. Experiments demonstrate that the proposed algorithm improves speech …
Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt
Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, …
An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding
An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Edge computing is a new paradigm that provides data processing capabilities at the network edge. In view of the uneven data distribution and the constrained onboard resource, an edge device often needs to call for a number of neighboring devices as followers to cooperate on data analysis tasks. However, these followers may be rational and selfish, having their private optimization objectives such as energy efficiency. Therefore, the leader device needs to incentivize the followers to achieve a certain global objective, e.g., maximizing task accomplishment, rather than their own objectives. In this paper, we model the aforementioned challenges in edge computing …
Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant
Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Human activity recognition (HAR) is a critical process for applications that focus on the classification of human physical activities such as jogging, walking, downstairs, and upstairs. Ordinal classification (OC) is a special type of supervised multi-class classification in which an inherent ordering among the classes exists, such as low, medium, and high. This study combines these two concepts and introduces an approach to ?human activity recognition based on ordinal classification? (HAROC). In the proposed approach, ordinal classification is applied to human activity recognition where the physical activities can be ordered by using their signals? band power values. This is the …
Simultaneous Feedforward Online Command Rate Limiter Filters For Existingcontrollers, Gali̇p Serdar Tombul
Simultaneous Feedforward Online Command Rate Limiter Filters For Existingcontrollers, Gali̇p Serdar Tombul
Turkish Journal of Electrical Engineering and Computer Sciences
One of the biggest challenges in controller design for a mechatronics system is the actuator limitations. Either response time of the actuator or the input constraints creates limits for the controller performance and stability. In this study a novel feedforward online rate limiter scheme for arbitrary input signals is introduced by taking velocity, acceleration and jerk constraints into account, and it is investigated that how the control effort and system response is affected by the demand signal's rate of change limitations. A fin actuation system for a guided missile is given as an example where the demand signal comes from …
Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf
Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf
Turkish Journal of Electrical Engineering and Computer Sciences
This article presents a novel polarization-insensitive chipless radio frequency identification tag having an encoding capacity of 11 bits. The proposed resonator design comprises discontinuous arc slots forming truncated elliptically shape offering 1:1 slot to bit correspondence with suppressed unwanted harmonic resonances. Electromagnetic performance analysis of the proposed tag design is done over an ungrounded Rogers RT duroid® 5880 laminate. The overall tag design covers a footprint of 15 × 15 × 0.508 mm3 offering convincingly appreciable bit density of 4.88 bits/cm2 . The realized tags are analyzed for real-world electromagnetic performance resulting in an agreement between measured and computed results. …
An Mih-Enhanced Fully Distributed Mobility Management (Mf-Dmm) Solutionfor Real And Non-Real Time Cvbr Traffic Classes In Mobile Internet, Sankaranarayanan Parasuraman, Gayathri Rajaraman, Tamijetchelvy Ramachandiran
An Mih-Enhanced Fully Distributed Mobility Management (Mf-Dmm) Solutionfor Real And Non-Real Time Cvbr Traffic Classes In Mobile Internet, Sankaranarayanan Parasuraman, Gayathri Rajaraman, Tamijetchelvy Ramachandiran
Turkish Journal of Electrical Engineering and Computer Sciences
The integration of wireless access networks has progressed rapidly in recent years. Within the mobile communication environment, the operator provides multiple interface options for the mobile node (MN) to switch its connection to any access network during mobility to achieve the quality of service (QoS) for various traffic classes. The conventional centralised mobility management (CMM) scheme lacks reliability, dynamic anchoring and a single point of failure. This stimulates the distributed mobility management (DMM) scheme to handle mobility at the access network rather in a centralised manner. Therefore, in this paper, an IEEE 802.21 media independent handover (MIH) enhanced fully DMM …
Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant
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 …
Clustered Mobile Data Collection In Wsns: An Energy-Delay Trade-Of, İzzet Fati̇h Şentürk
Clustered Mobile Data Collection In Wsns: An Energy-Delay Trade-Of, İzzet Fati̇h Şentürk
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks enable monitoring remote areas with limited human intervention. However, the network connectivity between sensor nodes and the base station (BS) may not be always possible due to the limited transmission range of the nodes. In such a case, one or more mobile data collectors (MDCs) can be employed to visit nodes for data collection. If multiple MDCs are available, it is desirable to minimize the energy cost of mobility while distributing the cost among the MDCs in a fair manner. Despite availability of various clustering algorithms, there is no single fits all clustering solution when different requirements …
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
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 …
New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin
New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin
Turkish Journal of Electrical Engineering and Computer Sciences
The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things …
A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli
A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli
Turkish Journal of Electrical Engineering and Computer Sciences
The COVID-19 pandemic has caused millions of deaths and changed daily life globally. Countries have declared a half or full lockdown to prevent the spread of COVID-19. According to medical doctors, as many people as possible should be tested to identify their status, and corresponding actions then should be taken for COVID-19 positive cases. Despite the clear necessity of these medical tests, many countries are still struggling to acquire them. This fact clearly indicates the necessity of a large-scale, cheap, fast, and accurate alternative prescreening tool that can be used for the diagnosis of COVID-19 while waiting for the medical …
A Novel Method For Soc Estimation Of Li-Ion Batteries Using A Hybrid Machinelearning Technique, Eymen İpek, Murat Yilmaz
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 …
Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems provide recommendations to users using background data such as ratings of users about items and features of items. These systems are used in several areas such as e-commerce, news websites, and article websites. By using recommender systems, customers are provided with relevant data as soon as possible and are able to make good decisions. There are more studies about recommender systems and improving their performance. In this study, prediction performances of neural networks are evaluated and their performances are improved using genetic algorithms. Performances obtained in this study are compared with those of other studies. After that, superiority …
Time-Oriented Interactive Process Miner: A New Approach For Time Prediction, İsmai̇l Yürek, Derya Bi̇rant, Özlem Ece Yürek, Kökten Ulaş Bi̇rant
Time-Oriented Interactive Process Miner: A New Approach For Time Prediction, İsmai̇l Yürek, Derya Bi̇rant, Özlem Ece Yürek, Kökten Ulaş Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Everyday information systems collect a different kind of process instances of a business flow. As time goes on, the size of the collected data builds up speedily and constitutes a huge amount of data. It is a very challenging task to obtain valuable information and features of processes from such big data. Considering in advance, the trend and different features of the ongoing process are essential. Especially, time management is crucial in designing and conducting business processes. In this article, a novel process miner algorithm is proposed for time prediction, named time-oriented İnteractive process miner (T-IPM), which predicts the remaining …
Abnormal Behavior Detection Using Sparse Representations Through Sequentialgeneralization Of K-Means, Ahlam Aldhamari, Rubita Sudirman, Nasrul Humaimi Mahmood
Abnormal Behavior Detection Using Sparse Representations Through Sequentialgeneralization Of K-Means, Ahlam Aldhamari, Rubita Sudirman, Nasrul Humaimi Mahmood
Turkish Journal of Electrical Engineering and Computer Sciences
The potential capability to automatically detect and classify human behavior as either normal or abnormal events is an important aspect in intelligent monitoring/surveillance systems. This study presents a new high-performance framework for detecting behavioral abnormalities in video streams by utilizing only the patterns for normal behaviors. In this paper, we used a hybrid descriptor, called a foreground optical flow energy (FGOFE), which makes use of two effective motion techniques in order to extract the most descriptive spatiotemporal features in video sequences. The FGOFE descriptor can effectively capture both weak and sudden incidents in a scene. The sequential generalization of k-means …
A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r
A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
This study proposes a new approach that combines stability and optimization in the design of proportional? integral (PI) controller of automatic voltage regulators (AVR) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AVR system, has been designed. The approach follows a method investigating the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AVR system?s parameters have changed. The stability boundary locus (SBL) method is a graphic-based …
A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan
A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan
Turkish Journal of Electrical Engineering and Computer Sciences
High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data …
Performance Improvement Of The Shunt Active Power Filter Using A Novel Adaptivefiltering Approach, Abderrezzaq Zoghbi, Daoud Berkani
Performance Improvement Of The Shunt Active Power Filter Using A Novel Adaptivefiltering Approach, Abderrezzaq Zoghbi, Daoud Berkani
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces an efficient control approach to enhance harmonics mitigation performance of the shunt active power filter (SAPF). This approach is based on adaptive filters favored by their built-in automatic parameters adaptation capability. The proposed filter, which uses a variable leaky least mean square (VLLMS) adaptation, is applied with a modified instantaneous power PQ theory. This enhances its dynamic performance over the use of conventional time-invariant filters, and overcomes its limitations in the presence of nonsinusoidal voltage conditions. The studied SAPF model is simulated in MATLAB/SIMULINK with combinations of nonlinear and unbalanced loads. Simulation results indicate a significant improvement …
A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k
A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k
Turkish Journal of Electrical Engineering and Computer Sciences
Removal of hair using laser is a widely used method, where our goal is to permanently remove hair by using laser to cause heat in order to thermally damage the hair follicle. However, currently available laser hair removal systems affect the outer skin layers besides hair follicles. This is a disadvantage of classical methods with major health risks. We propose a method to overcome these health risks by guiding the laser beam only to automatically localized hair regions. This study aims to develop an automated feature-based hair region localization method as an integral part of the proposed hair removal system …
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Under the noncascade structure, the balance between q-axis current constraint and dynamic performance in permanent-magnet synchronous motor system has become a critical problem. On the one hand, large transient current is required to provide high torque to achieve fast dynamic performance. On the other hand, current constraint becomes a state constraint problem, instead of governing q-axis reference current in the cascade structure directly. Aiming at this issue, a novel fast terminal sliding mode control (FTSMC)-based controller with current constraint is developed in this paper. The novelty of this scheme is related to the proposed penalty function based on interior point …
Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca
Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca
Turkish Journal of Electrical Engineering and Computer Sciences
IEEE 802.11ax as the newest wireless local area networks (WLANs) standard brings enormous improvements in network throughput, coverage and energy efficiency in densely populated areas. Unlike previous IEEE 802.11 WLAN standards where power saving mechanisms have a limited capability and flexibility, 802.11ax comes with a different mechanism called target wake time (TWT) where stations (STAs) wake up only after each TWT interval and different STAs can wake up at different time instance depending on their application requirements. As an example, for a periodic data arrival occurring in IoT applications, STA can wake up by following the data period and go …
Impact Of Hybrid Power Generation On Voltage, Losses, And Electricity Cost Indistribution Networks, Yavuz Ateş, Tayfur Gökçek, Ahmet Yi̇ği̇t Arabul
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 …
Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek
Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek
Turkish Journal of Electrical Engineering and Computer Sciences
Moving from internal combustion engine based towards electric based transportation is crucial for wide societies as they facilitate the use of green energy technologies such as wind and solar. Interior mounted permanent magnet (IPM) machines, also known as salient brushless alternating current (AC) machines, are commonly employed in traction applications as they have superior features, such as high efficiency operation, high torque, and power densities. The efficiency optimization in IPM drives is achieved by obtaining and operating at accurate and unique current angle for a certain electromagnetic torque demand. In conventional drives, the optimum current angle is obtained by online …
Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez
Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez
Turkish Journal of Electrical Engineering and Computer Sciences
Pneumonia is one of the major diseases that cause a lot of deaths all over the world. Determining pneumonia from chest X-ray (CXR) images is an extremely difficult and important image processing problem. The discrimination of whether pneumonia is of bacterium or virus origin has also become more important during the pandemic. Automatic determination of the presence and origin of pneumonia is crucial for speeding up the treatment process and increasing the patient's survival rate. In this study, a convolutional neural network (CNN) framework is proposed for detection of pneumonia from CXR images. Two different binary CNNs and a triple …
Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r
Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
This paper is concerned with the modeling framework based on power and control for a mechanical system that has nonlinear, unstable, and under-actuated characteristic features, based on an analogy, which is developed by using the Brayton and Moser's (BM) equations between mechanical and electrical systems. The analogy is based on a mixed-potential function generalized for BM. The mixed-potential function for a cart - pole double inverted pendulum (CPDIP) system is used as a new building block for modeling, analysis, and controller design. The analogy allows for the exact transfer of results from electrical circuit synthesis and analysis to the mechanical …
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl
Turkish Journal of Electrical Engineering and Computer Sciences
Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …
Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar
Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar
Turkish Journal of Electrical Engineering and Computer Sciences
The cyclic prefix (CP) is a prefix technique widely used in orthogonal frequency division multiplexing (OFDM) systems in order to eliminate the intersymbol interference (ISI) caused by the dispersion of wireless channels. However, CP reduces the number of symbols that can be transmitted in one OFDM symbol. Therefore, CP is one of the bottlenecks of OFDM systems limiting their spectral efficiency (SE). This limitation on the SE of the classical CP-based OFDM system is the main motivation for this work to introduce a novel method. In this paper, the design of a new CP structure, which is based on the …
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken
Turkish Journal of Electrical Engineering and Computer Sciences
Generative adversarial networks (GANs) can be used in a wide range of applications where drawing samples from a data probability distribution without explicitly representing it is essential. Unlike the deep convolutional neural networks (CNNs) trained for mapping an input to one of the multiple outputs, monitoring the overfitting and underfitting in GANs is not trivial since they are not classifying but generating a data. While training set and validation set accuracy give a direct sense of success in terms of overfitting and underfitting for CNNs during the training process, evaluating the GANs mainly depends on the visual inspection of the …