| 基于有理平方根B样条模型的概率密度函数形状控制 |
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| 引用本文： | 周靖林, 岳红, 王宏. 基于有理平方根B样条模型的概率密度函数形状控制. 自动化学报, 2005, 31(3): 343-351. |
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| 作者姓名： | 周靖林 岳红 王宏 |
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| 作者单位： | 1.Institute of Automation, Chinese Academy of Sciences, Beijing 100080 |
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| 摘 要： | This paper presents a new method for the modeling and control of the output probability density functions (PDFs) of linear stochastic systems. At first, a new PDF approximation method, namely the rational square-root B-spline model is proposed and the innovative concept of pseudoweights is introduced. The new model is then compared with the existing B-spline models in terms of feasible domains. Next, a controller is developed to realize the output PDF tracking performance. An alternative minimal entropy control strategy is also provided for the case that no target PDF is available. Finally, illustrative examples indicate the effectiveness of the proposed algorithms.
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| 关 键 词： | Dynamic stochastic systems probability density function (PDF) B-spline neural network robust control minimum entropy control |
| 收稿时间： | 2003-11-10 |
| 修稿时间： | 2004-06-05 |
Shaping of Output PDF Based on the Rational Square-root B-spline Model |
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| ZHOU Jing-Lin, YUE Hong, WANG Hong. Shaping of Output PDF Based on the Rational Square-root B-spline Model. ACTA AUTOMATICA SINICA, 2005, 31(3): 343-351. |
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| Authors: | ZHOU Jing-Lin YUE Hong WANG Hong |
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| Affiliation: | 1. Institute of Automation, Chinese Academy of Sciences, Beijing 100080 |
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| Abstract: | This paper presents a new method for the modeling and control of the output probability density functions (PDFs) of linear stochastic systems. At first, a new PDF approximation method, namely the rational square-root B-spline model is proposed and the innovative concept of pseudoweights is introduced. The new model is then compared with the existing B-spline models in terms of feasible domains. Next, a controller is developed to realize the output PDF tracking performance. An alternative minimal entropy control strategy is also provided for the case that no target PDF is available. Finally, illustrative examples indicate the effectiveness of the proposed algorithms. |
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| Keywords: | Dynamic stochastic systems probability density function (PDF) B-spline neural network robust control minimum entropy control |
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