{"title":"Modeling and behavioral analysis of noise characteristics of a 4th order Phase - Locked Loop","authors":"","doi":"10.3906/elk-1908-85","DOIUrl":"https://doi.org/10.3906/elk-1908-85","url":null,"abstract":"","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"498 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75208484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Madhusmita Mohanty, S. Selvakumar, C. Koodalsamy, S. P. Simon
Global maximum operating point (GMOP) tracking is an important requirement of solar photovoltaic (PV) systems under partial shading conditions (PSCs). Though the perturb and observe algorithm is simple and effective, it fails to recognize the GMOP. This paper explores the application of the firefly algorithm (FA) to the maximum power point tracking (MPPT) problem of PV systems. In order to determine the shortest path to reach the GMOP under various PSCs, a new fast convergence firefly algorithm (FA) is proposed. Additionally, the change in firefly position is limited to a maximum value identified based on the characteristics of the PSC. The fast convergence method is guaranteed to find the GMOP, avoiding the local operating point obstacle through a repeated space search technique. Using MATLAB, the algorithm is implemented on a model PV system. An experimental 300-W PV system is developed to validate the operating point of the PV system under various PSCs. The proposed method is tested on a 5-kW solar power plant. The results demonstrate that the proposed MPPT algorithm outperforms particle swarm optimization, FA-based MPPTs, and other methods available in the literature.
{"title":"Global maximum operating point tracking for PV system using fast convergence Firefly algorithm","authors":"Madhusmita Mohanty, S. Selvakumar, C. Koodalsamy, S. P. Simon","doi":"10.3906/elk-1805-108","DOIUrl":"https://doi.org/10.3906/elk-1805-108","url":null,"abstract":"Global maximum operating point (GMOP) tracking is an important requirement of solar photovoltaic (PV) systems under partial shading conditions (PSCs). Though the perturb and observe algorithm is simple and effective, it fails to recognize the GMOP. This paper explores the application of the firefly algorithm (FA) to the maximum power point tracking (MPPT) problem of PV systems. In order to determine the shortest path to reach the GMOP under various PSCs, a new fast convergence firefly algorithm (FA) is proposed. Additionally, the change in firefly position is limited to a maximum value identified based on the characteristics of the PSC. The fast convergence method is guaranteed to find the GMOP, avoiding the local operating point obstacle through a repeated space search technique. Using MATLAB, the algorithm is implemented on a model PV system. An experimental 300-W PV system is developed to validate the operating point of the PV system under various PSCs. The proposed method is tested on a 5-kW solar power plant. The results demonstrate that the proposed MPPT algorithm outperforms particle swarm optimization, FA-based MPPTs, and other methods available in the literature.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"27 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78120600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees’ activities through their reflection on social media. Moreover, this dataset facilitates a number of further and deeper analyses of the refugees in Turkey.
{"title":"Refugees’ social media activities in Turkey: a computational analysis and demonstration method","authors":"M. A. Bülbül, S. Ismail","doi":"10.3906/ELK-1804-9","DOIUrl":"https://doi.org/10.3906/ELK-1804-9","url":null,"abstract":"This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees’ activities through their reflection on social media. Moreover, this dataset facilitates a number of further and deeper analyses of the refugees in Turkey.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"12 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78344439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, technical details of a Stewart platform (SP) based robotic system as an endoscope positioner and holder for endoscopic transsphenoidal surgery are presented. Inverse and forward kinematics, full dynamics, and the Jacobian matrix of the robotic system are derived and simulated in MATLAB/Simulink. The required control structure for the trajectory and position control of the SP is developed and verified by several experiments. The robotic system can be navigated using a six degrees of freedom (DOF) joystick and a haptic device with force feedback. Position and trajectory control of the SP in the joint space is achieved using a new model-free intelligent PI (iPI) controller and it is compared with the classical PID (proportional-integral-derivative) controller. Trajectory tracking experimental results showed that the tracking performance of iPI is better than that of PID and the total RMSE of the trajectory tracking is decreased by 17.64% using the iPI controller. The validity of the robotic system is proven in the endoscopic transsphenoidal surgery performed on a realistic head model in the laboratory and on a cadaver in the Institute of Forensic Medicine. The key feature of the system developed here is to operate the endoscope via the joystick or haptic device with force feedback under iPI control. Usage of this system helps surgeons in long, fatiguing, and complex operations. This system can generate new possibilities for transsphenoidal surgery such as fully automated robotic surgery systems.
{"title":"Design and development of a Stewart platform assisted and navigated transsphenoidal surgery","authors":"S. Kizir, Z. Bingül","doi":"10.3906/ELK-1608-145","DOIUrl":"https://doi.org/10.3906/ELK-1608-145","url":null,"abstract":"In this study, technical details of a Stewart platform (SP) based robotic system as an endoscope positioner and holder for endoscopic transsphenoidal surgery are presented. Inverse and forward kinematics, full dynamics, and the Jacobian matrix of the robotic system are derived and simulated in MATLAB/Simulink. The required control structure for the trajectory and position control of the SP is developed and verified by several experiments. The robotic system can be navigated using a six degrees of freedom (DOF) joystick and a haptic device with force feedback. Position and trajectory control of the SP in the joint space is achieved using a new model-free intelligent PI (iPI) controller and it is compared with the classical PID (proportional-integral-derivative) controller. Trajectory tracking experimental results showed that the tracking performance of iPI is better than that of PID and the total RMSE of the trajectory tracking is decreased by 17.64% using the iPI controller. The validity of the robotic system is proven in the endoscopic transsphenoidal surgery performed on a realistic head model in the laboratory and on a cadaver in the Institute of Forensic Medicine. The key feature of the system developed here is to operate the endoscope via the joystick or haptic device with force feedback under iPI control. Usage of this system helps surgeons in long, fatiguing, and complex operations. This system can generate new possibilities for transsphenoidal surgery such as fully automated robotic surgery systems.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"16 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78357909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.
{"title":"Structure tensor adaptive total variation for image restoration","authors":"S. Prasath, D. Thanh","doi":"10.3906/ELK-1802-76","DOIUrl":"https://doi.org/10.3906/ELK-1802-76","url":null,"abstract":"Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"81 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81015473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ground vehicle detection and classification with distributed sensor networks is of growing interest for border security. Different sensing modalities including electro-optical, seismic, and acoustic were evaluated individually and in combination to develop a more efficient system. Despite previous works that mostly studied frequency-domain features and acoustic sensors, in this work we analyzed the classification performance for both frequency and time-domain features and seismic and acoustic modalities. Despite their infrequent use, we show that when fused with frequency-domain features, time-domain features improve the classification performance and reduce the false positive rate, especially for seismic signals. We investigated the performance of seismic sensors and showed that the classification performance varies with the type of road due to the distinct spectral characteristics of the medium. Our proposed classifier fuses time and frequency-domain features and acoustic and seismic modalities to achieve the highest classification rate of 98.6% using a relatively small number of features.
{"title":"A new spectral estimation-based feature extraction method for vehicle classification in distributed sensor networks","authors":"Erdem Köse, A. K. Hocaoglu","doi":"10.3906/ELK-1807-49","DOIUrl":"https://doi.org/10.3906/ELK-1807-49","url":null,"abstract":"Ground vehicle detection and classification with distributed sensor networks is of growing interest for border security. Different sensing modalities including electro-optical, seismic, and acoustic were evaluated individually and in combination to develop a more efficient system. Despite previous works that mostly studied frequency-domain features and acoustic sensors, in this work we analyzed the classification performance for both frequency and time-domain features and seismic and acoustic modalities. Despite their infrequent use, we show that when fused with frequency-domain features, time-domain features improve the classification performance and reduce the false positive rate, especially for seismic signals. We investigated the performance of seismic sensors and showed that the classification performance varies with the type of road due to the distinct spectral characteristics of the medium. Our proposed classifier fuses time and frequency-domain features and acoustic and seismic modalities to achieve the highest classification rate of 98.6% using a relatively small number of features.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88634656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish language, and these studies have lower performance results compared to those studies for English. The reasons for this can be incorrect translation of datasets from English into Turkish and ignoring the special grammar structures in the latter. In this study, special Turkish words and linguistic constructs which affect the polarity of a sentence are determined with the aid of a Turkish linguist, and an appropriate lexicon-based polarity determination and calculation approach is introduced for this language. The proposed methodology is tested using different datasets collected from Twitter, and the test results show that the proposed system achieves better accuracy than the previously developed lexical-based sentiment analysis systems for Turkish. The authors conclude that especially analysis of word groups increases the overall performance of the system significantly.
{"title":"A polarity calculation approach for lexicon-based Turkish sentiment analysis","authors":"Gökhan Yurtalan, Murat Koyuncu, Ç. Turhan","doi":"10.3906/ELK-1803-92","DOIUrl":"https://doi.org/10.3906/ELK-1803-92","url":null,"abstract":"Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish language, and these studies have lower performance results compared to those studies for English. The reasons for this can be incorrect translation of datasets from English into Turkish and ignoring the special grammar structures in the latter. In this study, special Turkish words and linguistic constructs which affect the polarity of a sentence are determined with the aid of a Turkish linguist, and an appropriate lexicon-based polarity determination and calculation approach is introduced for this language. The proposed methodology is tested using different datasets collected from Twitter, and the test results show that the proposed system achieves better accuracy than the previously developed lexical-based sentiment analysis systems for Turkish. The authors conclude that especially analysis of word groups increases the overall performance of the system significantly.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"31 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89886964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we proposed a lexicon for emotion analysis in Turkish for six emotional categories happiness, fear, anger, sadness, disgust, and surprise. Besides, we also investigated the effects of a lemmatizer and a stemmer, two term-weighting schemes, four lexicon enrichment methods, and a term selection approach for lexicon construction. To do this, we generated Turkish emotion lexicon based on a dataset, TREMO, containing 25,989 documents. We then preprocessed the documents to obtain dictionary and stem forms of each term using a lemmatizer and a stemmer. Afterwards, we proposed two different weighting schemes where term frequency, term-class frequency and mutual information (MI) values for six emotion categories are taken into consideration. We then enriched the lexicon by using bigram and concept hierarchy methods, and performed term selection for efficiency issues. Then, we compared the performance of lexicon-based approach with machine learning based approach by using our proposed lexicon. The experiments showed that the use of the proposed lexicon efficiently produces comparable results in emotion analysis in Turkish text.
{"title":"Lexicon-based emotion analysis in Turkish","authors":"Mansur Alp Toçoğlu, A. Alpkocak","doi":"10.3906/ELK-1807-41","DOIUrl":"https://doi.org/10.3906/ELK-1807-41","url":null,"abstract":"In this paper, we proposed a lexicon for emotion analysis in Turkish for six emotional categories happiness, fear, anger, sadness, disgust, and surprise. Besides, we also investigated the effects of a lemmatizer and a stemmer, two term-weighting schemes, four lexicon enrichment methods, and a term selection approach for lexicon construction. To do this, we generated Turkish emotion lexicon based on a dataset, TREMO, containing 25,989 documents. We then preprocessed the documents to obtain dictionary and stem forms of each term using a lemmatizer and a stemmer. Afterwards, we proposed two different weighting schemes where term frequency, term-class frequency and mutual information (MI) values for six emotion categories are taken into consideration. We then enriched the lexicon by using bigram and concept hierarchy methods, and performed term selection for efficiency issues. Then, we compared the performance of lexicon-based approach with machine learning based approach by using our proposed lexicon. The experiments showed that the use of the proposed lexicon efficiently produces comparable results in emotion analysis in Turkish text.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"52 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90876577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Hossam-Eldin, A. Mansour, Mohammed Elgamal, K. Youssef
The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load profiles during the day’s cycle. The mitigation of the power quality issues manifested in current harmonics, voltage sag, and voltage swell is achieved through the implementation of a new fully fuzzy controlled unified power quality conditioner (UPQC). It is controlled by an energy management system (EMS). This paper introduces a new control system for the UPQC using full fuzzy logic control. Moreover, fuzzy control is used in current control instead of proportional integral controllers so that it has acceptable performance over a wide range of operating points. The novel approach of an EMS-connected UPQC activates the UPQC at the required time only into the grid. This approach has many benefits by increasing the UPQC lifetime. The effect of the proposed system on the aforementioned issues has been validated through simulation by MATLAB/Simulink. The results are compared with those obtained by conventional methods. The results verify the superior performance of the proposed UPQC to mitigate the problems of current total harmonic distortions, voltage sag, and voltage swell under different operating conditions during the monitoring period.
{"title":"Power quality improvement of smart microgrids using EMS-based fuzzy controlled UPQC","authors":"A. Hossam-Eldin, A. Mansour, Mohammed Elgamal, K. Youssef","doi":"10.3906/ELK-1807-166","DOIUrl":"https://doi.org/10.3906/ELK-1807-166","url":null,"abstract":"The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load profiles during the day’s cycle. The mitigation of the power quality issues manifested in current harmonics, voltage sag, and voltage swell is achieved through the implementation of a new fully fuzzy controlled unified power quality conditioner (UPQC). It is controlled by an energy management system (EMS). This paper introduces a new control system for the UPQC using full fuzzy logic control. Moreover, fuzzy control is used in current control instead of proportional integral controllers so that it has acceptable performance over a wide range of operating points. The novel approach of an EMS-connected UPQC activates the UPQC at the required time only into the grid. This approach has many benefits by increasing the UPQC lifetime. The effect of the proposed system on the aforementioned issues has been validated through simulation by MATLAB/Simulink. The results are compared with those obtained by conventional methods. The results verify the superior performance of the proposed UPQC to mitigate the problems of current total harmonic distortions, voltage sag, and voltage swell under different operating conditions during the monitoring period.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"11 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88712203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider a biobjective sequential decision-making problem where an allocation (arm) is called ε lexi- cographic optimal if its expected reward in the first objective is at most ε smaller than the highest expected reward, and its expected reward in the second objective is at least the expected reward of a lexicographic optimal arm. The goal of the learner is to select arms that are ε lexicographic optimal as much as possible without knowing the arm reward distributions beforehand. For this problem, we first show that the learner’s goal is equivalent to minimizing the ε lexicographic regret, and then, propose a learning algorithm whose ε lexicographic gap-dependent regret is bounded and gap-independent regret is sublinear in the number of rounds with high probability. Then, we apply the proposed model and algorithm for dynamic rate and channel selection in a cognitive radio network with imperfect channel sensing. Our results show that the proposed algorithm is able to learn the approximate lexicographic optimal rate–channel pair that simultaneously minimizes the primary user interference and maximizes the secondary user throughput.
{"title":"The biobjective multiarmed bandit: learning approximate lexicographic optimal allocations","authors":"Cem Tekin","doi":"10.3906/ELK-1806-221","DOIUrl":"https://doi.org/10.3906/ELK-1806-221","url":null,"abstract":"We consider a biobjective sequential decision-making problem where an allocation (arm) is called ε lexi- cographic optimal if its expected reward in the first objective is at most ε smaller than the highest expected reward, and its expected reward in the second objective is at least the expected reward of a lexicographic optimal arm. The goal of the learner is to select arms that are ε lexicographic optimal as much as possible without knowing the arm reward distributions beforehand. For this problem, we first show that the learner’s goal is equivalent to minimizing the ε lexicographic regret, and then, propose a learning algorithm whose ε lexicographic gap-dependent regret is bounded and gap-independent regret is sublinear in the number of rounds with high probability. Then, we apply the proposed model and algorithm for dynamic rate and channel selection in a cognitive radio network with imperfect channel sensing. Our results show that the proposed algorithm is able to learn the approximate lexicographic optimal rate–channel pair that simultaneously minimizes the primary user interference and maximizes the secondary user throughput.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"23 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87116381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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