ARMA 新息模型在最优滤波理论中起重要作用。
The ARMA innovation models play an important role in the optimal filtering.
作为滤波理论的应用，我们研究了一类部分可观测的递归线性二次最优控制问题。
As an application of filtering theory, we study one kind of partially observed linear quadratic recursive optimal control problem.
在最优滤波器理论基础上，推导出离散域的最优平滑算子，抑制了图像的分割错误、噪声和伪边缘的影响。
The smooth operator is inferred based on the Optimal Discrete Filter's theory, which can reduce the influence of noise, false edges and image error.
根据博弈理论与最优控制理论，提出一种能够在具有不确定噪声干扰中最小化滤波误差的极小极大值鲁棒滤波器。
Based on the game theory and LQG optimal control theory, the mini-max robust filtering is presented, which can minimize the filtering errors under the disturbance of uncertain noises.
利用CTRANC抑制干扰信号的特性及语音信号的短时稳定性，借助最优控制相关理论，得到了新的语音分离方法及其自适应滤波迭代步长的计算公式。
Based on the CTRANC characteristic of suppressing the interfering signal and stability in short-term of speech signal, an adaptive speech separation algorithm based on the CTRANC system comes out.
利用CTRANC抑制干扰信号的特性及语音信号的短时稳定性，借助最优控制相关理论，得到了新的语音分离方法及其自适应滤波迭代步长的计算公式。
Based on the CTRANC characteristic of suppressing the interfering signal and stability in short-term of speech signal, an adaptive speech separation algorithm based on the CTRANC system comes out.
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