Recursive filtering and smoothing for reciprocal Gaussian processes with Dirichlet boundary conditions
Recursive filtering and smoothing for reciprocal Gaussian processes with Dirichlet boundary conditions
复制标题
具有狄利克雷边界条件的倒数高斯过程的递归滤波和平滑
DOI：
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发表时间：
1998
影响因子：
5.4
通讯作者：
R. Cusani
中科院分区：
文献类型：
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作者：
E. Baccarelli;R. Cusani
在有噪声观测的Dirichlet随机边界条件下，完全解决了受加性白高斯噪声影响的离散指数倒数高斯过程的最小均方误差估计问题。得到了用于计算滤波序列、定点、固定区间和固定滞后平滑序列的有限组递归方程。文中还给出了所提出估计器的最小均方误差性能的递推表达式。仿真结果验证了性能分析的有效性。
The minimum mean square error (MMSE) estimation problem for a discrete-index reciprocal Gaussian process impaired by additive white Gaussian noise is completely solved in the general case of noisily observed Dirichlet random boundary conditions. Finite sets of recursive equations are obtained for the computation of the filtered sequence and of the fixed-point, fixed-interval, and fixed-lag smoothed sequences. Recursive expressions are also given for the MMSE performance of the presented estimators. Simulation results confirm the validity of the performance analysis.