2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT)最新文献_第2页

Computer Model of Radio Frequency Power Amplifier 射频功率放大器的计算机模型

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678673

O. Pliushch, Yu. K. Kravchenko, O. Matviichuk-Yudina, Anatolii Rybydajlo, Oleksandr Trush, Roman A. Mykolaichuk

{"title":"Computer Model of Radio Frequency Power Amplifier","authors":"O. Pliushch, Yu. K. Kravchenko, O. Matviichuk-Yudina, Anatolii Rybydajlo, Oleksandr Trush, Roman A. Mykolaichuk","doi":"10.1109/ATIT54053.2021.9678673","DOIUrl":"https://doi.org/10.1109/ATIT54053.2021.9678673","url":null,"abstract":"Processes in output circuits of radiofrequency power amplifiers are considered. It is shown that traditional analytical methods of their performance analysis are complex and time-consuming. Application of computer simulation in MATLAB environment for studying performance of radiofrequency power amplifiers is proposed. A model of a tuned output circuit of the class C power amplifier is designed. This model accounts for resonance properties of the tuned circuit as well active losses in it. Verification of the model was carried out for standard situations using well-known formulas for amplitudes of harmonic components. Verification results clearly show validity of the model. For example, when it comes to harmonic components, the model has an error around half a percent. The designed model was used to study the circuit performance in two scenarios of interest and obtained results conform to the theoretical interpretations of the processes in radiofrequency amplifiers. The designed model clearly, graphically and with high precision shows the processes unfolding in the output circuits of the power amplifier. It can be used to study performance of the power amplifiers and to search for ways to improve their characteristics.","PeriodicalId":368050,"journal":{"name":"2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121756528","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

The Method of Solving Problems of Optimal Restoration of Telecommunication Signals 电信信号最优恢复问题的求解方法

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678649

H. Vlasyk, I. Zamrii, V. Shkapa, Serhii Laptiev, Alla Kalyniuk, Tetiana Laptieva

引用次数: 10

Information Theory and Technologies Security 信息理论与技术安全“，

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/atit54053.2021.9678768

引用次数: 0

Creating a Mathematical Model for Estimating the Impact of Errors in the Process of Reconstruction of Non-Uniform Code Structures on the Quality of Recoverable Video Images 建立了非均匀码结构重构过程中误差对可恢复视频图像质量影响的数学模型

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678887

O. Yudin, V. Artemov, A. Krasnorutsky, V. Barannik, Ivan Tupitsya, Gennady Pris

引用次数: 6

The Complex Method of Coreferent Pairs Detection in a Ukrainian-language Text Based on a BiLSTM Neural Network 基于BiLSTM神经网络的乌克兰语文本共指对复数检测方法

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678674

S. Telenyk, S. Pogorilyy, A. Kramov

{"title":"The Complex Method of Coreferent Pairs Detection in a Ukrainian-language Text Based on a BiLSTM Neural Network","authors":"S. Telenyk, S. Pogorilyy, A. Kramov","doi":"10.1109/ATIT54053.2021.9678674","DOIUrl":"https://doi.org/10.1109/ATIT54053.2021.9678674","url":null,"abstract":"Coreference resolution is one of the background tasks in the area of natural language processing. As this task falls into the category of AI-complete problems, different machine learning techniques are used in order to solve it with sufficient accuracy. In this paper, a new complex method of coreferent clusters detection based on a BiLSTM neural network has been suggested. The state-of-the-art methods of coreference resolution have been considered. The impact of the different features of a text on the accuracy of the detection of coreferent pairs has been investigated. It has been shown that the semantic representation of mentions should be considered as the main component during the preparation of input data for a model. The neural network based on a shared BiLSTM layer has been designed and trained using a SEARN-based approach. The set of filtering sieves has been used as an additional instrument for the detection of explicit connections between coreferent objects. The experimental verification of the effectiveness of the suggested method has been performed using corresponding metrics. The results obtained may indicate that the proposed method can be utilized in order to group the coreferent objects into clusters for the different Slavic language corpora.","PeriodicalId":368050,"journal":{"name":"2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452898","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

Forecast Model of Technical State of Telecommunication System: Intelligent Statistical Data Processing 电信系统技术状态预测模型:智能统计数据处理

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678738

O. Yudin, V. Artemov, Maksym Tyshchenko, Yevhenii Makhno, N. Tarasenko, Oleksandr Shapran

引用次数: 2

Model of the Sensor Network Based on Unmanned Aerial Vehicle 基于无人机的传感器网络模型

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678623

Oleksandr Trush, Ivan Kravchenko, M. Trush, O. Pliushch, A. Dudnik, Kateryna Shmat

引用次数: 1

Methodology for Calculating Information Protection from Parameters of its Distribution in Social Networks 基于社交网络信息分布参数的信息保护计算方法

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678599

V. Savchenko, V. Akhramovych, T. Dzyuba, Serhii Laptiev, N. Lukova-Chuiko, Tetiana Laptieva

{"title":"Methodology for Calculating Information Protection from Parameters of its Distribution in Social Networks","authors":"V. Savchenko, V. Akhramovych, T. Dzyuba, Serhii Laptiev, N. Lukova-Chuiko, Tetiana Laptieva","doi":"10.1109/ATIT54053.2021.9678599","DOIUrl":"https://doi.org/10.1109/ATIT54053.2021.9678599","url":null,"abstract":"The article investigated dynamic models of the information security system in social networks, taking into account indicators of information dissemination in the social network, as well as analyzed the stability of the protection system.There is a practical interest in researching the behavior of the social network protection system against the value of indicators of information dissemination. The study is based on the nonlineability of the social network protection system. Theoretical study of the dynamic behavior of a real object requires the creation of its mathematical model. The procedure for developing a model consists in drawing up mathematical equations based on physical laws. These laws are formulated in the language of differential equations. As a result, the coordinates of the system state and its parameters were interconnected, which allows you to start solving differential equations under different initial conditions and parameters.To solve the system of nonlinear equations used: method of exceptions, joint solution of the corresponding homogeneous characteristic equation.Phase portraits of the data protection system in MatLab/Multisim are defined, which indicate the stability of the protection system in the working range of parameters even at the maximum impact value.","PeriodicalId":368050,"journal":{"name":"2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116136463","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: 5

Methods of Designing Adaptive Systems of Multilevel Monitoring and Diagnosis for Recognition and Forecasting of Technological Condition of Complex Technical Objects 复杂技术对象技术状态识别与预测的多层次自适应监测诊断系统设计方法

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678591

Nadiia Marchenko, O. Nechyporuk, Olha Suprun, Oksana Martynova, O. Suprun, M. Melnyk

引用次数: 4

Integrated Model of Positioning and Situation Monitoring System Using LoRa, WiFi, GSM Technology 基于LoRa、WiFi、GSM技术的定位与态势监控系统集成模型

2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT) Pub Date : 2021-12-15 DOI: 10.1109/ATIT54053.2021.9678693

O. Tymochko, Yu.О. Afanasiev, Vadym Fustii, V. Afanasiev, Serhii Fediuk, Boris Telyatnik

引用次数: 1