{"title":"建模与估计方法在非线性状态空间模型系统辨识中的应用综述","authors":"Xiaonan Li, Ping Ma, Tao Chao, Ming Yang","doi":"10.1142/s179396232350054x","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Review of the Application of Modeling and Estimation method in System Identification for Nonlinear State-space Models\",\"authors\":\"Xiaonan Li, Ping Ma, Tao Chao, Ming Yang\",\"doi\":\"10.1142/s179396232350054x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":50871,\"journal\":{\"name\":\"Advances in Complex Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Complex Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s179396232350054x\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Complex Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s179396232350054x","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
期刊介绍:
Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.