Non-Gaussian noise quadratic estimation for linear discrete-time time-varying systems

Non-Gaussian noise quadratic estimation for linear discrete-time time-varying systems
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线性离散时间时变系统的非高斯噪声二次估计

DOI:
10.1016/j.neucom.2015.10.015
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发表时间:
2016-01
期刊:
影响因子:
6
通讯作者:
Zhang, Chenghui
Zhang, Chenghui
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zhao, Huihong;Zhang, Chenghui

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研究线性离散非高斯系统输入噪声的二次多项式估计问题。首先将非高斯噪声二次反卷积滤波器和固定滞后平滑器的设计转化为一个适当的二阶多项式扩展系统的线性估计问题。利用Kronecker代数规则,讨论了增广系统中增广噪声的随机特性。然后利用卡尔曼滤波理论中的投影公式,得到了非高斯噪声二次估计量的一种求解方法。此外,通过构造具有不相关噪声的等价状态空间模型,证明了系统的稳定性。最后通过数值算例验证了该方法的有效性。
This study deals with the input noise quadratic polynomial estimation problem for linear discrete-time non-Gaussian systems. The design of the non-Gaussian noise quadratic deconvolution filter and fixed-lag smoother is firstly converted into a linear estimation problem in a suitable second-order polynomial extended system. By employing the Kronecker algebra rules, the stochastic characteristics of the augmented noise in the augmented system are discussed. Then a solution to the non-Gaussian noise quadratic estimator is obtained through applying the projection formula in Kalman filtering theory. In addition, the stability is proved by constructing an equivalent state-space model with uncorrelated noises. Finally, a numerical example is given to show the effectiveness of the proposed method.
DOI: 10.1002/acs.1133
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