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nonparametricapproachtoidentifyingnarxsystems
Qijiang SONG; HanFu CH1N
2010
Source Publicationjournalofsystemsscienceandcomplexity
ISSN1009-6124
Volume000Issue:001Pages:3
AbstractThis paper considers identification of the nonlinear autoregression with exogenous inputs (NARX system). The growth rate of the nonlinear function is required be not faster than linear with slope less than one. The value of f(·) at any fixed point is recursively estimated by the stochastic approximation (SA) algorithm with the help of kernel functions. Strong consistency of the estimates is established under reasonable conditions, which, in particular, imply stability of the system. The numerical simulation is consistent with the theoretical analysis.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/37334
Collection中国科学院数学与系统科学研究院
Affiliation中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Qijiang SONG,HanFu CH1N. nonparametricapproachtoidentifyingnarxsystems[J]. journalofsystemsscienceandcomplexity,2010,000(001):3.
APA Qijiang SONG,&HanFu CH1N.(2010).nonparametricapproachtoidentifyingnarxsystems.journalofsystemsscienceandcomplexity,000(001),3.
MLA Qijiang SONG,et al."nonparametricapproachtoidentifyingnarxsystems".journalofsystemsscienceandcomplexity 000.001(2010):3.
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