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2021 29th Signal Processing and Communications Applications Conference (SIU)最新文献

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A Comparative Analysis for Binary Search Operators used in Artificial Bee Colony 人工蜂群中二元搜索算子的比较分析
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477907
Ibrahim Atli, R. Durgut, Mehmet Emin Aydin
{"title":"A Comparative Analysis for Binary Search Operators used in Artificial Bee Colony","authors":"Ibrahim Atli, R. Durgut, Mehmet Emin Aydin","doi":"10.1109/SIU53274.2021.9477907","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477907","url":null,"abstract":"Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications on metaheuristic approaches or utilization of various operators. Some of these operators help fast convergence at the beginning but lose efficiency relatively or completely towards the end or vice versa. The individual and collective behaviors of operators in the search space plays crucial role in producing fruitful solutions to approximate the optimum and to devise useful adaptive selection schemes in the cases of using multiple operators. To the best of our knowledge, collective behaviour of binary operators has not been analysed comprehensively. In this study, the characteristics and collective behaviour of operators that can work on discrete decision variables within an artificial bee colony are investigated over solving OneMax and SUKP problems utilizing 9 different operators. The results conclude that disABC, GBABC and twoOptABC operators are more effective in solving OneMax problems, while GBABC and twoOptABC are more effective (especially towards end) in the SUKP problems.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131454588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Outage Probability of Satellite-Terrestrial Systems with In-Band Full-Duplex Relay 带内全双工中继星地系统的中断概率
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9478014
Okan Ertürk, I. Altunbas
{"title":"Outage Probability of Satellite-Terrestrial Systems with In-Band Full-Duplex Relay","authors":"Okan Ertürk, I. Altunbas","doi":"10.1109/SIU53274.2021.9478014","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9478014","url":null,"abstract":"In this study, in-band full-duplex multiple-antenna hybrid satellite-terrestrial cooperative systems are proposed, and an analysis is carried out on the outage probability (OP). In the study, uplink and downlink scenarios are considered and their OPs are derived as a closed-form expression in terms of the Meijer-G function of two variables. In addition, asymptotic analysis is performed to determine the parameters affecting the OP for the high signal-to-noise ratio region. The theoretical analyses have been confirmed by testing with computer simulations.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134044915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine Learning Aided Demodulator in MISO Beamforming Systems MISO波束形成系统中的机器学习辅助解调器
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477826
Melis Çetintürk, Yavuz Adam, Caner Göztepe, Günes Karabulut-Kurt
{"title":"Machine Learning Aided Demodulator in MISO Beamforming Systems","authors":"Melis Çetintürk, Yavuz Adam, Caner Göztepe, Günes Karabulut-Kurt","doi":"10.1109/SIU53274.2021.9477826","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477826","url":null,"abstract":"In this study, a machine learning (ML) aided demodulator was designed for equalization and demodulation of the signal at the receiver in a multiple-input single-output (MISO) beamforming system. To observe the accuracy of MLaided demodulator in the presence of Rayleigh channel; XGBoost, LightGBM, and Linear Support Vector Machine (SVM) algorithms are used. Several scenarios were discussed where the number of antennas, signal-to-noise ratio (SNR), channel perfection, and channel information availability changed. As a result of 72 different measurements, it was observed that Linear SVM operates at slightly lower bit error rate (BER) levels among 3 algorithms. However, the SVM has higher time complexity and could not provide a significant advantage over other algorithms. Therefore, the use of the LightGBM algorithm, with a very low amount of BER sacrifice, greatly reduces time complexity.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131640079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Perlin Random Erasing for Data Augmentation 数据增强的柏林随机擦除
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477804
Murat Saran, Fatih Nar, Ayşe Nurdan Saran
{"title":"Perlin Random Erasing for Data Augmentation","authors":"Murat Saran, Fatih Nar, Ayşe Nurdan Saran","doi":"10.1109/SIU53274.2021.9477804","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477804","url":null,"abstract":"In the last decade, Deep Learning is applied in a wide range of problems with tremendous success. Large data, increased computational resources, and theoretical improvements are main reasons for this success. As the dataset grows, the realworld is better represented, allows developing a model that can generalize. However, creating a labeled dataset is expensive, timeconsuming, or sometimes even challenging. Therefore, researchers proposed data augmentation methods to increase dataset size by creating variations of the existing data. This study proposes an extension to Random Erasing data augmentation method by introducing smoothness. The proposed method provides better performance compared to Random Erasing data augmentation method, which is shown using a transfer learning scenario on the UC Merced Land-use image dataset.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132596349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
A CNN Based Super-Resolution Technique for Magnetic Particle Imaging System Matrix 基于CNN的磁粒子成像系统矩阵超分辨率技术
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477772
Barıis Aşkın, A. Güngör, D. Soydan, C. B. Top, T. Çukur
{"title":"A CNN Based Super-Resolution Technique for Magnetic Particle Imaging System Matrix","authors":"Barıis Aşkın, A. Güngör, D. Soydan, C. B. Top, T. Çukur","doi":"10.1109/SIU53274.2021.9477772","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477772","url":null,"abstract":"Magnetic Particle Imaging (MPI) is a new imaging technique that allows high resolution & high frame-rate imaging of super-paramagnetic iron-oxide (SPIOs) particles. The imaging process can be modeled linearly. However, due to non-idealities and variations of the experimental system in time, many MPI systems first measure the forward model matrix (i.e. calibrate the system), then reconstruct frames from the measurements using these matrices. The image resolution and size is directly affected by the size of the system matrix. However, the calibration process may consume a lot of time depending on the field of view and resolution. In this study, we propose applying superresolution techniques on measured low-resolution system matrices to get to high resolution system matrices. Here, we propose a convolutional neural network (CNN) based super-resolution technique tailored for MPI, and show its effectiveness against linear interpolation. The methods are compared in a noiseless simulation environment, and for a super-resolution factor of 4×4, our proposed technique resulted in %2.92 normalized Root Mean Squared Error (nRMSE), while bicubic interpolation techniques resulted in %12.47 nRMSE.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130864979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Simulation of Unmanned Aerial Vehicle for Mapping 无人机测绘仿真研究
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477834
B. Turan, S. Turhan, Özgün Pinarer, Elif Bozkaya
{"title":"Simulation of Unmanned Aerial Vehicle for Mapping","authors":"B. Turan, S. Turhan, Özgün Pinarer, Elif Bozkaya","doi":"10.1109/SIU53274.2021.9477834","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477834","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) is a flying vehicle that is physically unmanned, controlled by a ground-based controller with a remote control or can be moved autonomous or semi-autonomous depending on a flight plan. The use of UAVs has become widespread in recent years thanks to the development of technology and making them more accessible. The ability of UAVs to produce high accuracy 3D data and orthophoto images at low cost has also enabled the development of UAV photogrammetry. UAV-based systems are used in many fields such as agriculture, forestry, urban planning, earth events and disaster management, especially for military purposes. In this study, a simulation environment was created for the “Parrot Mini Drone”, a mini quadcopter that can withstand environmental conditions, has an adaptable, motion stability, and can shoot video at the same time, and a 3-dimensional model of an area where visual data is collected was obtained. With this study, developed using MATLAB & Simulink, a three-dimensional map of a specific area was created with the help of a quadcopter.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133058279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Simultaneous Localization and Mapping with One Particle 一个粒子的同时定位和映射
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9478047
Yasin YenIaydin, Semih Köklücan
{"title":"Simultaneous Localization and Mapping with One Particle","authors":"Yasin YenIaydin, Semih Köklücan","doi":"10.1109/SIU53274.2021.9478047","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9478047","url":null,"abstract":"Rao-Blackwellized particle filter (RBPF) is one of the powerful techniques for simultaneous localization and mapping (SLAM) since it factorizes the posteriors over the maps and potential trajectories of the robot. RBPF has its own advantages as well as disadvantages. RBPF approach has a major problem with computational complexity and this is related to the number of the particles. Thus, reducing the number of particles is one of the biggest challenges in RBPF. In this study, one particle based on the proposal distribution is computed by utilizing the most likely pose obtained by a scan matching procedure. Next, grid search around the most likely pose is performed to search for better pose. Furthermore, the proposal distribution does not depend on the odometry model and formulation of computing the probability of the sensor model is given. After that, mapping is built based on the computed pose. Lastly, accuracybased quantitative and qualitative results by utilizing 2D LIDAR performed in computer simulations show the efficacy of this method.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115447740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
LSTM and GRU based Traffic Prediction Using Live Network Data 基于LSTM和GRU的实时网络流量预测
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9478011
Evren Tuna, A. Soysal
{"title":"LSTM and GRU based Traffic Prediction Using Live Network Data","authors":"Evren Tuna, A. Soysal","doi":"10.1109/SIU53274.2021.9478011","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9478011","url":null,"abstract":"Artificial Intelligence can help 5G and Beyond networks to manage the complexity as a result of integration of different technologies and the design requirement specific to vertical needs. With this paradigm, it is essential to predict the network metrics in order to be prepared for future demand in the network. In this paper, we have focused on RNN based traffic volume prediction of an eNodeB. We use live network metrics to train our multivariable forcasting model to analyze the traffic demand and predict the network traffic by using LSTM and GRU models. Our results show the importance of multi-variable approach and that both models can handle the demand increase in busy hours of days when the traffic load is in line with its periodical trend. Sudden increases or decreases in traffic load may sometimes create problem such as prediction of more or less resources than required. GRU performs better to handle sudden increase or decrease situations.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115476791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Tympanic Membrane Generation with Generative Adversarial Networks 基于生成对抗网络的鼓膜生成
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477848
M. Eseoglu, M. Karsligil, I. Koçak
{"title":"Tympanic Membrane Generation with Generative Adversarial Networks","authors":"M. Eseoglu, M. Karsligil, I. Koçak","doi":"10.1109/SIU53274.2021.9477848","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477848","url":null,"abstract":"Obtaining sufficient original data in most studies in the field of medical pattern recognition is a difficult and time consuming process. Different data augmentation methods are used to increase the amount of data to be used to train these systems. In this study, a generative adversarial networks based system that produces artificial images by using the tympanic membrane images taken from otoscope devices for data augmentation has been designed and trained. Artificial images that has been generated by different generative adversarial networks have been evaluated by specialist physicians with a Visual Turing test. Preliminary results show that artificial medical images can be perceived as real with high confidence scores.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115826089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The Fractional Version of a Multi-Wing Chaotic System and Its Circuit Synthesis 多翼混沌系统的分数型及其电路合成
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477944
Ibrahim Ethem Saçu, N. Korkmaz
{"title":"The Fractional Version of a Multi-Wing Chaotic System and Its Circuit Synthesis","authors":"Ibrahim Ethem Saçu, N. Korkmaz","doi":"10.1109/SIU53274.2021.9477944","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477944","url":null,"abstract":"In this study, it has been focused on a fractional version of a chaotic system that is defined by three state variables, is autonomous and has a multi-wing atractor characteristic. The minimum fractional-order of this multi-wing and fractional-order chaotic system has been determined by the stability analysis. The numerical response of this system has been obtained by the Grünwald-Letnikov method by selecting a fractional order that is higher than the determined minimum fractional degree. Then, a third-order approximation function is calculated for this chaotic system by using the Matsudo method, and an imitation circuit has been designed by using this calculated function. This designed circuit has been adapted to the circuit structure that is proposed for the multi-wing chaotic system. The efficiency of the obtained final circuit has been verified by comparing the numerical simulation results and the responses of the revealed circuit structure.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114515257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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