| Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIR model简 |
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| 引用本文： | Jing CHEN,Rui-feng DING. Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIR model简[J]. 浙江大学学报:C卷英文版, 2014, 15(2): 147-152. DOI: 10.1631/jzus.C1300072 |
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| 作者姓名： | Jing CHEN Rui-feng DING |
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| 基金项目： | Project supported by the National Natural Science Foundation of China （No. 60973043） and the Natural Science Foundation of Jiangsu Province, China （No. BK20131109） |
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| 摘 要： | Based on the work in Ding and Ding （2008）, we develop a modifi ed stochastic gradient （SG） parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two fi nite impulse response （FIR） models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.
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| 关 键 词： | Parameter estimation Auxiliary model Dual-rate system Stochastic gradient Box-Jenkins model FIR model |
Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIRmode |
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| Jing Chen,Rui-feng Ding. Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIRmode[J]. Journal of Zhejiang University-Science C(Computers and Electronics), 2014, 15(2): 147-152. DOI: 10.1631/jzus.C1300072 |
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| Authors: | Jing Chen Rui-feng Ding |
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| Affiliation: | 1. School of Science, Jiangnan University, Wuxi, 214122, China
2. School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, China
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| Abstract: | Based on the work in Ding and Ding (2008), we develop a modified stochastic gradient (SG) parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two finite impulse response (FIR) models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective. |
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