{"title":"有限时间内多正弦信号的参数估计","authors":"Tung Nguyen Khac, S. Vlasov, A. Pyrkin","doi":"10.35470/2226-4116-2022-11-2-74-81","DOIUrl":null,"url":null,"abstract":"The problems of identifying the frequency and parameters of multi-sinusoidal signals with constant parameters are considered in finite time. The signal is represented as the output of a linear generator, where the parameters of the sinusoidal signal (amplitude, phase, and frequency) are unknown. The main idea is to apply the Jordan waveform and lag to parameterize the signal and obtain a linear regression model. Unknown parameters are estimated using DREM method. The performance of algorithms considered in the article is illustrated by computer modeling. Our main contribution is to propose a new approach for parameterization of multisinusoidal signals and finite time parameter estimation.","PeriodicalId":37674,"journal":{"name":"Cybernetics and Physics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parameters estimation of multi-sinusoidal signal in finite-time\",\"authors\":\"Tung Nguyen Khac, S. Vlasov, A. Pyrkin\",\"doi\":\"10.35470/2226-4116-2022-11-2-74-81\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problems of identifying the frequency and parameters of multi-sinusoidal signals with constant parameters are considered in finite time. The signal is represented as the output of a linear generator, where the parameters of the sinusoidal signal (amplitude, phase, and frequency) are unknown. The main idea is to apply the Jordan waveform and lag to parameterize the signal and obtain a linear regression model. Unknown parameters are estimated using DREM method. The performance of algorithms considered in the article is illustrated by computer modeling. Our main contribution is to propose a new approach for parameterization of multisinusoidal signals and finite time parameter estimation.\",\"PeriodicalId\":37674,\"journal\":{\"name\":\"Cybernetics and Physics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cybernetics and Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35470/2226-4116-2022-11-2-74-81\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybernetics and Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35470/2226-4116-2022-11-2-74-81","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Physics and Astronomy","Score":null,"Total":0}
Parameters estimation of multi-sinusoidal signal in finite-time
The problems of identifying the frequency and parameters of multi-sinusoidal signals with constant parameters are considered in finite time. The signal is represented as the output of a linear generator, where the parameters of the sinusoidal signal (amplitude, phase, and frequency) are unknown. The main idea is to apply the Jordan waveform and lag to parameterize the signal and obtain a linear regression model. Unknown parameters are estimated using DREM method. The performance of algorithms considered in the article is illustrated by computer modeling. Our main contribution is to propose a new approach for parameterization of multisinusoidal signals and finite time parameter estimation.
期刊介绍:
The scope of the journal includes: -Nonlinear dynamics and control -Complexity and self-organization -Control of oscillations -Control of chaos and bifurcations -Control in thermodynamics -Control of flows and turbulence -Information Physics -Cyber-physical systems -Modeling and identification of physical systems -Quantum information and control -Analysis and control of complex networks -Synchronization of systems and networks -Control of mechanical and micromechanical systems -Dynamics and control of plasma, beams, lasers, nanostructures -Applications of cybernetic methods in chemistry, biology, other natural sciences The papers in cybernetics with physical flavor as well as the papers in physics with cybernetic flavor are welcome. Cybernetics is assumed to include, in addition to control, such areas as estimation, filtering, optimization, identification, information theory, pattern recognition and other related areas.