Kalman filtering is an optimum filtering employing the norm of minimum mean square error.
卡尔曼滤波采用最小均方误差准则，是一种最优滤波。
The paper proposes a nonparameter data extrapolation method based on minimum variance spectrum estimation and minimum weighted norm constraint.
提出一种最小方差谱估计和最小加权范数约束结合的非参数类数据外推方法。
It presents a least side length weight inverse method of traverse for minimum norm estimate without iteration.
提出一个不需要迭代的最小范数估计的导线最小侧边权逆法。
The method absorbs the advantages of the gradient projection method and minimum norm method.
该方法吸收了梯度投影法和最小范数法的优点。
A new hybrid minimum norm solution in frequency domain was also considered, which is better in suppressing the impact of noise on error separation th...
介绍了圆度误差分离中的频域最小范数混合解，这种混合解比最小二乘解和最小均方误差解具有更好的噪声抑制效果。
In this paper the error analysis is conducted. It presents a least side length weight inverse method of traverse for minimum norm estimate without iteration.
本文进行误差分析。提出一个不需要迭代的最小范数估计的导线最小侧边权逆法。
A method for parameter optimization is presented. The minimum-norm of state feedback matrix and optimal pole assignment also are studied in this paper.
本文提出一种参数最优化的方法，对状态反馈阵最小范数问题和最优极点配置问题进行了探讨。
In the test stage, the sensing matrix is projected onto the test vector, and the minimum l0-norm solution is computed with Orthogonal Matching Pursuit (omp) algorithm.
利用正交匹配跟踪算法求最小零范数解，在变换域中用近邻法判断测试数据的类别。
Its coordinate parameter estimate value possesses uniqueness; non - deviation and mInimum norm. Consequently. it is the most rational computing method.
其坐标参数估值具有唯一性、无偏性和最小范数性，因此，它是最合理的算法。
The important methods of analysis TMS evoked brain responses include: waveform analysis, spectral analysis, global mean field amplitude (GMFA), minimum-norm estimation (MNE), and so on.
的翻译是：tms的重要分析方法引起脑部反应包括：波形分析、频谱分析、全球的平均字段振幅(gmfa)，最小的标准估计(多国企业)，以此类推。
The important methods of analysis TMS evoked brain responses include: waveform analysis, spectral analysis, global mean field amplitude (GMFA), minimum-norm estimation (MNE), and so on.
的翻译是：tms的重要分析方法引起脑部反应包括：波形分析、频谱分析、全球的平均字段振幅(gmfa)，最小的标准估计(多国企业)，以此类推。
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